Data engineering Martech Privacy & compliance

Custom customer data platform: full control of your customer data

A customer data platform (CDP) brings together customer data from all your systems into a single, unified profile. We build custom CDPs for organisations that want more than a generic SaaS solution: a platform that fits your data model, your compliance requirements and your existing martech stack exactly, and that makes you the owner of your own first-party data.

Discuss your CDP challenge See our approach
Unified Customer Profile Web events CRM App events E-mail platform Offline / POS Personalisatie Advertenties

From data silos to unified customer profiles

Most organisations know a great deal about their customers, but that knowledge is spread across dozens of systems that don't talk to each other. Website analytics sits apart from the CRM, which sits apart from the email platform, which sits apart from the e-commerce back end. The result is that each department works with its own, incomplete picture of the customer. A CDP resolves this by bringing all that data together into one persistent profile per customer. See also our API integration services and our work on enterprise AI implementation.

How we build a CDP

We start with a discovery phase in which we map out your data sources, data models and activation goals. We then build iteratively: first the data ingestion pipeline and the unified profile model, then identity resolution, then the segmentation layer, and finally the activation channels. Each component is tailored to your existing stack and compliance requirements.

Where SaaS CDPs force you to pour your data into their model, we build the model around your data. That is the fundamental difference between a generic tool and a platform that truly understands your business.

1. Discovery & data model
2. Data ingestion & pipeline
3. Identity resolution
4. Segmentation & audience builder
5. Activation & integrations

Core components of a custom CDP

A CDP is not a single application but a set of layers, each fulfilling a specific role. We build each component with the right technology for your scale and use cases, and ensure all layers work together seamlessly.

Ingest

Data ingestion & event streaming

All customer interactions are collected from your sources in real time or in batches. We build robust ingestion pipelines that validate, normalise and store data without data loss, even during peaks in volume.

  • Event streaming via Apache Kafka
  • SDK integration for web & mobile
  • Batch imports for CRM and ERP
  • Webhook and API connectors
Profile

Identity resolution & unified profile

The heart of any CDP: recognising the same customer across different devices, sessions and channels. We design an identity resolution strategy that suits your data, from deterministic matching on email address to probabilistic models.

  • Deterministic identity resolution
  • Persistent unified customer profiles
  • Cross-device and cross-channel matching
  • Profile merging with audit trail
Activation

Segmentation & data activation

A CDP is only valuable if the data is usable. We build an audience builder that lets marketers define segments based on behaviour, attributes and scores, and activate those segments to downstream systems without involving the data team.

  • Visual audience builder
  • Real-time segment updates
  • Activation to email, ads and personalisation
  • Loading predictive scores per profile

What you can do with a unified customer profile

The value of a CDP lies not in the technology itself but in what you can do with it. Unified profiles open up possibilities that are simply out of reach with fragmented data. See also our work on headless commerce platforms and business intelligence tools.

E-commerce

Omnichannel personalisation

When you know that a visitor to your website also opened an email yesterday and bought a product three weeks ago, you can tailor the website experience, the next email and any advertisements to that context. That is personalisation based on genuine customer history, not on session cookies.

A CDP makes it possible to share customer context across channels in real time: as soon as someone makes a purchase through the app, your email platform sees it in the next campaign run.

Retention

Churn prediction & loyalty programmes

With a complete customer profile, you can recognise patterns that precede churn: logging in less often, falling purchase frequency, not opening campaigns. You can automatically translate those signals into a personalised retention action, such as a targeted offer, proactive customer service outreach or a loyalty bonus.

Connect the CDP to predictive analytics to calculate churn scores per customer and automatically activate the right segments.

Media & advertising

First-party audience activation

With the phasing out of third-party cookies, advertisers are increasingly dependent on their own customer data. A CDP is the infrastructure with which you build first-party audiences and synchronise them directly to Google Ads, Meta and other advertising platforms.

You decide for yourself which customers fall into which segment, based on genuine behavioural data rather than age brackets or interests that an external platform guesses.

Analysis

Customer lifetime value & cohort analysis

A unified profile makes it possible to analyse the full customer lifecycle, from first point of contact to most recent purchase. You can compare cohorts, calculate lifetime value per acquisition source and see which behavioural patterns correlate with high CLV.

These analyses are immediately available to your BI tool or analytics dashboard, because the CDP feeds the data warehouse with structured, clean profile data.

Technology behind a custom CDP

We choose technology based on your scale, your team's expertise and your infrastructure, not an opinionated stack that forces you to replace everything. See also our platform engineering and e-commerce development services.

Data ingestion & processing

For real-time event streaming we work with Apache Kafka or cloud-native alternatives such as AWS Kinesis or Google Pub/Sub. We build batch pipelines on Apache Spark or dbt, depending on the nature of the transformations and the required frequency. We implement stream processing for real-time profile updates with Flink or Kafka Streams.

  • Apache Kafka for event streaming
  • dbt for data transformations
  • Apache Flink for stream processing
  • AWS Kinesis / Google Pub/Sub
  • Airbyte for batch data integration

Storage, API & activation

Unified profiles are stored in a combination of a profile store (Redis or DynamoDB for real-time lookups) and an analytical store (BigQuery, Snowflake or Redshift) for historical analysis. The activation layer consists of a REST and GraphQL API that downstream systems call, supplemented with webhook triggers for real-time activation based on events. For AI-driven personalisation, we connect the CDP to ML models for score calculation.

  • Redis / DynamoDB for profile lookups
  • BigQuery, Snowflake or Redshift as analytical warehouse
  • REST and GraphQL APIs for activation
  • Webhook engine for real-time triggers
  • Python / Node.js backend, PostgreSQL

Why choose Appfront for your customer data platform?

We build CDPs as custom software, not as implementations of an existing SaaS product. This means we start from your business challenge and your data reality, not from the limitations of a tool.

Our principles

Your data, your infrastructure, your rules. No vendor lock-in, no per-profile fees, and no restrictions on what you can do with your own customer data.

Data ownership by design

Software expertise & data engineering

A CDP is not just a data project but also a software project: SDKs need to be built, APIs designed, dashboards created and pipelines monitored. As software developers and platform engineers, we have all the disciplines required within a single team.

  • Data engineering, backend and frontend in one team
  • No coordination between multiple agencies required
  • Architecture advice based on your existing stack

Handover & documentation

We do not build black boxes. Every architectural decision is documented, every pipeline is testable and day-to-day management can be transferred to your internal team. Once the project is complete, you will not depend on us for daily operations. Explore our full range of services or get in touch.

  • Complete architecture documentation
  • Automated tests for pipelines and APIs
  • Knowledge transfer to your team

Privacy by design & GDPR compliance as the foundation

A CDP processes sensitive personal data. We integrate privacy by design as an architectural principle, not as an afterthought. Also read our information security policy.

  • Consent management at the core of the data model
  • Data minimisation: only what is necessary is stored
  • Automatic data retention and deletion based on policy
  • Technical APIs for data subject rights (access, rectification, erasure)
  • Data residency in the Netherlands or the EU
  • Data processing agreement architecture with third parties mapped out
  • Audit logging of profile changes for demonstrable compliance
  • Encryption in transit and at rest as standard

The GDPR requires not only that you process data correctly, but also that you can demonstrate it. We build the technical infrastructure that provides that evidence: not paper policies, but enforceable technical controls.

Privacy by design

Frequently asked questions about building a customer data platform

What exactly is a customer data platform? +
A customer data platform (CDP) is a software layer that brings customer data from all touchpoints (website, app, CRM, email, point of sale, customer service) together into a single, consistent customer profile. Where separate systems each form their own silo, a CDP provides a shared and up-to-date view of every customer, available to all downstream systems that need it. The concept is covered in depth by platforms such as Segment in their CDP guide, but a custom CDP goes further because it fits precisely with your own data model and infrastructure.
What is the difference between a CDP, DMP and CRM? +
A CRM is primarily for managing customer relationships and sales processes: contacts, deals and interactions that your team records manually. A DMP (data management platform) works with anonymous, mainly third-party cookies for advertising purposes, a category that is losing considerable relevance as third-party cookies are phased out. A CDP works with first-party, identified customer data and builds persistent, rich profiles that can be used for personalisation, analytics and activation across all channels. In practice, a CDP and a CRM complement each other: the CRM manages the sales relationship, while the CDP manages the digital behavioural profile.
Why a custom CDP rather than a SaaS solution? +
SaaS CDPs such as Segment or mParticle are powerful but have structural limitations: fixed data models, high costs at scale (often per event or per profile), limited customisability of identity resolution, and dependence on their infrastructure for sensitive customer data. A custom CDP fits your data model, your compliance requirements and your existing stack precisely, and scales on your own terms. It is an investment that makes sense once your data volumes grow, your compliance requirements are specific, or your use cases diverge from what a standard tool offers.
How do you ensure GDPR compliance in the CDP? +
GDPR compliance is not a layer added afterwards but a design principle. We build consent management into the core of the data model: every profile carries its consent status, data minimisation determines which fields are stored, and retention rules are enforced through automated processes. Data subject rights (access, correction, erasure) are supported by technical APIs that your customer service team or self-service portal can call. Data processing agreements and data residency in the Netherlands or the EU are standard parts of the architecture. See also our information security policy.
Which systems can a CDP be integrated with? +
A CDP is by nature an integration layer. Typical sources include: website analytics (via a JavaScript SDK), mobile apps (via a mobile SDK), CRM systems, email platforms, e-commerce back-ends, till and POS systems, customer service tools and offline data sources via batch import. Typical destinations include: email platforms (Mailchimp, Klaviyo, Salesforce Marketing Cloud), advertising platforms (Google Ads, Meta), personalisation engines, analytics tools and data warehouses. The specific integrations depend on your existing martech stack. See also our API integration services.
What determines the cost of a custom CDP? +
The main factors are: the number of data sources and the quality of that data, the complexity of identity resolution (how difficult it is to recognise a customer across channels), the desired real-time processing speed, the number of downstream activation channels, and the compliance requirements. An MVP with core functionality requires a different investment than a fully developed platform with real-time streaming and multiple activation channels. After a discovery session, we prepare a clear proposal with phasing, so you can start with the core and expand when it becomes relevant. Get in touch for a no-obligation conversation.
How long does it take to build a customer data platform? +
An MVP with the core functionality — data ingestion from the key sources, unified profiles and one or two activation channels — is typically achievable in two to four months. A fully developed platform with real-time streaming, advanced segmentation, multiple integrations and a self-service audience builder takes longer, depending on the complexity of your data sources and your organisation. We work iteratively: after the first sprint you already have a working foundation with which you can begin testing and validating.

Ready to unify your customer data?

Start with a no-obligation conversation about your data challenge. We will analyse your current data sources, your activation goals and your compliance requirements, and give you a clear picture of what a custom CDP could mean for your organisation. Explore our services, read about our approach, or get in touch directly.

Discuss your CDP challenge Email us directly
✓ No-obligation introductory call • ✓ Privacy by design • ✓ No vendor lock-in • ✓ Data hosted in the Netherlands / EU
Data engineering Martech Privacy & compliance

Custom customer data platform: full control of your customer data

A customer data platform (CDP) brings together customer data from all your systems into a single, unified profile. We build custom CDPs for organisations that want more than a generic SaaS solution: a platform that fits your data model, your compliance requirements and your existing martech stack exactly, and that makes you the owner of your own first-party data.

Discuss your CDP challenge See our approach
Unified Customer Profile Web events CRM App events E-mail platform Offline / POS Personalisatie Advertenties

From data silos to unified customer profiles

Most organisations know a great deal about their customers, but that knowledge is spread across dozens of systems that don't talk to each other. Website analytics sits apart from the CRM, which sits apart from the email platform, which sits apart from the e-commerce back end. The result is that each department works with its own, incomplete picture of the customer. A CDP resolves this by bringing all that data together into one persistent profile per customer. See also our API integration services and our work on enterprise AI implementation.

How we build a CDP

We start with a discovery phase in which we map out your data sources, data models and activation goals. We then build iteratively: first the data ingestion pipeline and the unified profile model, then identity resolution, then the segmentation layer, and finally the activation channels. Each component is tailored to your existing stack and compliance requirements.

Where SaaS CDPs force you to pour your data into their model, we build the model around your data. That is the fundamental difference between a generic tool and a platform that truly understands your business.

1. Discovery & data model
2. Data ingestion & pipeline
3. Identity resolution
4. Segmentation & audience builder
5. Activation & integrations

Core components of a custom CDP

A CDP is not a single application but a set of layers, each fulfilling a specific role. We build each component with the right technology for your scale and use cases, and ensure all layers work together seamlessly.

Ingest

Data ingestion & event streaming

All customer interactions are collected from your sources in real time or in batches. We build robust ingestion pipelines that validate, normalise and store data without data loss, even during peaks in volume.

  • Event streaming via Apache Kafka
  • SDK integration for web & mobile
  • Batch imports for CRM and ERP
  • Webhook and API connectors
Profile

Identity resolution & unified profile

The heart of any CDP: recognising the same customer across different devices, sessions and channels. We design an identity resolution strategy that suits your data, from deterministic matching on email address to probabilistic models.

  • Deterministic identity resolution
  • Persistent unified customer profiles
  • Cross-device and cross-channel matching
  • Profile merging with audit trail
Activation

Segmentation & data activation

A CDP is only valuable if the data is usable. We build an audience builder that lets marketers define segments based on behaviour, attributes and scores, and activate those segments to downstream systems without involving the data team.

  • Visual audience builder
  • Real-time segment updates
  • Activation to email, ads and personalisation
  • Loading predictive scores per profile

What you can do with a unified customer profile

The value of a CDP lies not in the technology itself but in what you can do with it. Unified profiles open up possibilities that are simply out of reach with fragmented data. See also our work on headless commerce platforms and business intelligence tools.

E-commerce

Omnichannel personalisation

When you know that a visitor to your website also opened an email yesterday and bought a product three weeks ago, you can tailor the website experience, the next email and any advertisements to that context. That is personalisation based on genuine customer history, not on session cookies.

A CDP makes it possible to share customer context across channels in real time: as soon as someone makes a purchase through the app, your email platform sees it in the next campaign run.

Retention

Churn prediction & loyalty programmes

With a complete customer profile, you can recognise patterns that precede churn: logging in less often, falling purchase frequency, not opening campaigns. You can automatically translate those signals into a personalised retention action, such as a targeted offer, proactive customer service outreach or a loyalty bonus.

Connect the CDP to predictive analytics to calculate churn scores per customer and automatically activate the right segments.

Media & advertising

First-party audience activation

With the phasing out of third-party cookies, advertisers are increasingly dependent on their own customer data. A CDP is the infrastructure with which you build first-party audiences and synchronise them directly to Google Ads, Meta and other advertising platforms.

You decide for yourself which customers fall into which segment, based on genuine behavioural data rather than age brackets or interests that an external platform guesses.

Analysis

Customer lifetime value & cohort analysis

A unified profile makes it possible to analyse the full customer lifecycle, from first point of contact to most recent purchase. You can compare cohorts, calculate lifetime value per acquisition source and see which behavioural patterns correlate with high CLV.

These analyses are immediately available to your BI tool or analytics dashboard, because the CDP feeds the data warehouse with structured, clean profile data.

Technology behind a custom CDP

We choose technology based on your scale, your team's expertise and your infrastructure, not an opinionated stack that forces you to replace everything. See also our platform engineering and e-commerce development services.

Data ingestion & processing

For real-time event streaming we work with Apache Kafka or cloud-native alternatives such as AWS Kinesis or Google Pub/Sub. We build batch pipelines on Apache Spark or dbt, depending on the nature of the transformations and the required frequency. We implement stream processing for real-time profile updates with Flink or Kafka Streams.

  • Apache Kafka for event streaming
  • dbt for data transformations
  • Apache Flink for stream processing
  • AWS Kinesis / Google Pub/Sub
  • Airbyte for batch data integration

Storage, API & activation

Unified profiles are stored in a combination of a profile store (Redis or DynamoDB for real-time lookups) and an analytical store (BigQuery, Snowflake or Redshift) for historical analysis. The activation layer consists of a REST and GraphQL API that downstream systems call, supplemented with webhook triggers for real-time activation based on events. For AI-driven personalisation, we connect the CDP to ML models for score calculation.

  • Redis / DynamoDB for profile lookups
  • BigQuery, Snowflake or Redshift as analytical warehouse
  • REST and GraphQL APIs for activation
  • Webhook engine for real-time triggers
  • Python / Node.js backend, PostgreSQL

Why choose Appfront for your customer data platform?

We build CDPs as custom software, not as implementations of an existing SaaS product. This means we start from your business challenge and your data reality, not from the limitations of a tool.

Our principles

Your data, your infrastructure, your rules. No vendor lock-in, no per-profile fees, and no restrictions on what you can do with your own customer data.

Data ownership by design

Software expertise & data engineering

A CDP is not just a data project but also a software project: SDKs need to be built, APIs designed, dashboards created and pipelines monitored. As software developers and platform engineers, we have all the disciplines required within a single team.

  • Data engineering, backend and frontend in one team
  • No coordination between multiple agencies required
  • Architecture advice based on your existing stack

Handover & documentation

We do not build black boxes. Every architectural decision is documented, every pipeline is testable and day-to-day management can be transferred to your internal team. Once the project is complete, you will not depend on us for daily operations. Explore our full range of services or get in touch.

  • Complete architecture documentation
  • Automated tests for pipelines and APIs
  • Knowledge transfer to your team

Privacy by design & GDPR compliance as the foundation

A CDP processes sensitive personal data. We integrate privacy by design as an architectural principle, not as an afterthought. Also read our information security policy.

  • Consent management at the core of the data model
  • Data minimisation: only what is necessary is stored
  • Automatic data retention and deletion based on policy
  • Technical APIs for data subject rights (access, rectification, erasure)
  • Data residency in the Netherlands or the EU
  • Data processing agreement architecture with third parties mapped out
  • Audit logging of profile changes for demonstrable compliance
  • Encryption in transit and at rest as standard

The GDPR requires not only that you process data correctly, but also that you can demonstrate it. We build the technical infrastructure that provides that evidence: not paper policies, but enforceable technical controls.

Privacy by design

Frequently asked questions about building a customer data platform

What exactly is a customer data platform? +
A customer data platform (CDP) is a software layer that brings customer data from all touchpoints (website, app, CRM, email, point of sale, customer service) together into a single, consistent customer profile. Where separate systems each form their own silo, a CDP provides a shared and up-to-date view of every customer, available to all downstream systems that need it. The concept is covered in depth by platforms such as Segment in their CDP guide, but a custom CDP goes further because it fits precisely with your own data model and infrastructure.
What is the difference between a CDP, DMP and CRM? +
A CRM is primarily for managing customer relationships and sales processes: contacts, deals and interactions that your team records manually. A DMP (data management platform) works with anonymous, mainly third-party cookies for advertising purposes, a category that is losing considerable relevance as third-party cookies are phased out. A CDP works with first-party, identified customer data and builds persistent, rich profiles that can be used for personalisation, analytics and activation across all channels. In practice, a CDP and a CRM complement each other: the CRM manages the sales relationship, while the CDP manages the digital behavioural profile.
Why a custom CDP rather than a SaaS solution? +
SaaS CDPs such as Segment or mParticle are powerful but have structural limitations: fixed data models, high costs at scale (often per event or per profile), limited customisability of identity resolution, and dependence on their infrastructure for sensitive customer data. A custom CDP fits your data model, your compliance requirements and your existing stack precisely, and scales on your own terms. It is an investment that makes sense once your data volumes grow, your compliance requirements are specific, or your use cases diverge from what a standard tool offers.
How do you ensure GDPR compliance in the CDP? +
GDPR compliance is not a layer added afterwards but a design principle. We build consent management into the core of the data model: every profile carries its consent status, data minimisation determines which fields are stored, and retention rules are enforced through automated processes. Data subject rights (access, correction, erasure) are supported by technical APIs that your customer service team or self-service portal can call. Data processing agreements and data residency in the Netherlands or the EU are standard parts of the architecture. See also our information security policy.
Which systems can a CDP be integrated with? +
A CDP is by nature an integration layer. Typical sources include: website analytics (via a JavaScript SDK), mobile apps (via a mobile SDK), CRM systems, email platforms, e-commerce back-ends, till and POS systems, customer service tools and offline data sources via batch import. Typical destinations include: email platforms (Mailchimp, Klaviyo, Salesforce Marketing Cloud), advertising platforms (Google Ads, Meta), personalisation engines, analytics tools and data warehouses. The specific integrations depend on your existing martech stack. See also our API integration services.
What determines the cost of a custom CDP? +
The main factors are: the number of data sources and the quality of that data, the complexity of identity resolution (how difficult it is to recognise a customer across channels), the desired real-time processing speed, the number of downstream activation channels, and the compliance requirements. An MVP with core functionality requires a different investment than a fully developed platform with real-time streaming and multiple activation channels. After a discovery session, we prepare a clear proposal with phasing, so you can start with the core and expand when it becomes relevant. Get in touch for a no-obligation conversation.
How long does it take to build a customer data platform? +
An MVP with the core functionality — data ingestion from the key sources, unified profiles and one or two activation channels — is typically achievable in two to four months. A fully developed platform with real-time streaming, advanced segmentation, multiple integrations and a self-service audience builder takes longer, depending on the complexity of your data sources and your organisation. We work iteratively: after the first sprint you already have a working foundation with which you can begin testing and validating.

Ready to unify your customer data?

Start with a no-obligation conversation about your data challenge. We will analyse your current data sources, your activation goals and your compliance requirements, and give you a clear picture of what a custom CDP could mean for your organisation. Explore our services, read about our approach, or get in touch directly.

Discuss your CDP challenge Email us directly
✓ No-obligation introductory call • ✓ Privacy by design • ✓ No vendor lock-in • ✓ Data hosted in the Netherlands / EU
Data engineering Martech Privacy & compliance

Custom customer data platform: full control of your customer data

A customer data platform (CDP) brings together customer data from all your systems into a single, unified profile. We build custom CDPs for organisations that want more than a generic SaaS solution: a platform that fits your data model, your compliance requirements and your existing martech stack exactly, and that makes you the owner of your own first-party data.

Discuss your CDP challenge See our approach
Unified Customer Profile Web events CRM App events E-mail platform Offline / POS Personalisatie Advertenties

From data silos to unified customer profiles

Most organisations know a great deal about their customers, but that knowledge is spread across dozens of systems that don't talk to each other. Website analytics sits apart from the CRM, which sits apart from the email platform, which sits apart from the e-commerce back end. The result is that each department works with its own, incomplete picture of the customer. A CDP resolves this by bringing all that data together into one persistent profile per customer. See also our API integration services and our work on enterprise AI implementation.

How we build a CDP

We start with a discovery phase in which we map out your data sources, data models and activation goals. We then build iteratively: first the data ingestion pipeline and the unified profile model, then identity resolution, then the segmentation layer, and finally the activation channels. Each component is tailored to your existing stack and compliance requirements.

Where SaaS CDPs force you to pour your data into their model, we build the model around your data. That is the fundamental difference between a generic tool and a platform that truly understands your business.

1. Discovery & data model
2. Data ingestion & pipeline
3. Identity resolution
4. Segmentation & audience builder
5. Activation & integrations

Core components of a custom CDP

A CDP is not a single application but a set of layers, each fulfilling a specific role. We build each component with the right technology for your scale and use cases, and ensure all layers work together seamlessly.

Ingest

Data ingestion & event streaming

All customer interactions are collected from your sources in real time or in batches. We build robust ingestion pipelines that validate, normalise and store data without data loss, even during peaks in volume.

  • Event streaming via Apache Kafka
  • SDK integration for web & mobile
  • Batch imports for CRM and ERP
  • Webhook and API connectors
Profile

Identity resolution & unified profile

The heart of any CDP: recognising the same customer across different devices, sessions and channels. We design an identity resolution strategy that suits your data, from deterministic matching on email address to probabilistic models.

  • Deterministic identity resolution
  • Persistent unified customer profiles
  • Cross-device and cross-channel matching
  • Profile merging with audit trail
Activation

Segmentation & data activation

A CDP is only valuable if the data is usable. We build an audience builder that lets marketers define segments based on behaviour, attributes and scores, and activate those segments to downstream systems without involving the data team.

  • Visual audience builder
  • Real-time segment updates
  • Activation to email, ads and personalisation
  • Loading predictive scores per profile

What you can do with a unified customer profile

The value of a CDP lies not in the technology itself but in what you can do with it. Unified profiles open up possibilities that are simply out of reach with fragmented data. See also our work on headless commerce platforms and business intelligence tools.

E-commerce

Omnichannel personalisation

When you know that a visitor to your website also opened an email yesterday and bought a product three weeks ago, you can tailor the website experience, the next email and any advertisements to that context. That is personalisation based on genuine customer history, not on session cookies.

A CDP makes it possible to share customer context across channels in real time: as soon as someone makes a purchase through the app, your email platform sees it in the next campaign run.

Retention

Churn prediction & loyalty programmes

With a complete customer profile, you can recognise patterns that precede churn: logging in less often, falling purchase frequency, not opening campaigns. You can automatically translate those signals into a personalised retention action, such as a targeted offer, proactive customer service outreach or a loyalty bonus.

Connect the CDP to predictive analytics to calculate churn scores per customer and automatically activate the right segments.

Media & advertising

First-party audience activation

With the phasing out of third-party cookies, advertisers are increasingly dependent on their own customer data. A CDP is the infrastructure with which you build first-party audiences and synchronise them directly to Google Ads, Meta and other advertising platforms.

You decide for yourself which customers fall into which segment, based on genuine behavioural data rather than age brackets or interests that an external platform guesses.

Analysis

Customer lifetime value & cohort analysis

A unified profile makes it possible to analyse the full customer lifecycle, from first point of contact to most recent purchase. You can compare cohorts, calculate lifetime value per acquisition source and see which behavioural patterns correlate with high CLV.

These analyses are immediately available to your BI tool or analytics dashboard, because the CDP feeds the data warehouse with structured, clean profile data.

Technology behind a custom CDP

We choose technology based on your scale, your team's expertise and your infrastructure, not an opinionated stack that forces you to replace everything. See also our platform engineering and e-commerce development services.

Data ingestion & processing

For real-time event streaming we work with Apache Kafka or cloud-native alternatives such as AWS Kinesis or Google Pub/Sub. We build batch pipelines on Apache Spark or dbt, depending on the nature of the transformations and the required frequency. We implement stream processing for real-time profile updates with Flink or Kafka Streams.

  • Apache Kafka for event streaming
  • dbt for data transformations
  • Apache Flink for stream processing
  • AWS Kinesis / Google Pub/Sub
  • Airbyte for batch data integration

Storage, API & activation

Unified profiles are stored in a combination of a profile store (Redis or DynamoDB for real-time lookups) and an analytical store (BigQuery, Snowflake or Redshift) for historical analysis. The activation layer consists of a REST and GraphQL API that downstream systems call, supplemented with webhook triggers for real-time activation based on events. For AI-driven personalisation, we connect the CDP to ML models for score calculation.

  • Redis / DynamoDB for profile lookups
  • BigQuery, Snowflake or Redshift as analytical warehouse
  • REST and GraphQL APIs for activation
  • Webhook engine for real-time triggers
  • Python / Node.js backend, PostgreSQL

Why choose Appfront for your customer data platform?

We build CDPs as custom software, not as implementations of an existing SaaS product. This means we start from your business challenge and your data reality, not from the limitations of a tool.

Our principles

Your data, your infrastructure, your rules. No vendor lock-in, no per-profile fees, and no restrictions on what you can do with your own customer data.

Data ownership by design

Software expertise & data engineering

A CDP is not just a data project but also a software project: SDKs need to be built, APIs designed, dashboards created and pipelines monitored. As software developers and platform engineers, we have all the disciplines required within a single team.

  • Data engineering, backend and frontend in one team
  • No coordination between multiple agencies required
  • Architecture advice based on your existing stack

Handover & documentation

We do not build black boxes. Every architectural decision is documented, every pipeline is testable and day-to-day management can be transferred to your internal team. Once the project is complete, you will not depend on us for daily operations. Explore our full range of services or get in touch.

  • Complete architecture documentation
  • Automated tests for pipelines and APIs
  • Knowledge transfer to your team

Privacy by design & GDPR compliance as the foundation

A CDP processes sensitive personal data. We integrate privacy by design as an architectural principle, not as an afterthought. Also read our information security policy.

  • Consent management at the core of the data model
  • Data minimisation: only what is necessary is stored
  • Automatic data retention and deletion based on policy
  • Technical APIs for data subject rights (access, rectification, erasure)
  • Data residency in the Netherlands or the EU
  • Data processing agreement architecture with third parties mapped out
  • Audit logging of profile changes for demonstrable compliance
  • Encryption in transit and at rest as standard

The GDPR requires not only that you process data correctly, but also that you can demonstrate it. We build the technical infrastructure that provides that evidence: not paper policies, but enforceable technical controls.

Privacy by design

Frequently asked questions about building a customer data platform

What exactly is a customer data platform? +
A customer data platform (CDP) is a software layer that brings customer data from all touchpoints (website, app, CRM, email, point of sale, customer service) together into a single, consistent customer profile. Where separate systems each form their own silo, a CDP provides a shared and up-to-date view of every customer, available to all downstream systems that need it. The concept is covered in depth by platforms such as Segment in their CDP guide, but a custom CDP goes further because it fits precisely with your own data model and infrastructure.
What is the difference between a CDP, DMP and CRM? +
A CRM is primarily for managing customer relationships and sales processes: contacts, deals and interactions that your team records manually. A DMP (data management platform) works with anonymous, mainly third-party cookies for advertising purposes, a category that is losing considerable relevance as third-party cookies are phased out. A CDP works with first-party, identified customer data and builds persistent, rich profiles that can be used for personalisation, analytics and activation across all channels. In practice, a CDP and a CRM complement each other: the CRM manages the sales relationship, while the CDP manages the digital behavioural profile.
Why a custom CDP rather than a SaaS solution? +
SaaS CDPs such as Segment or mParticle are powerful but have structural limitations: fixed data models, high costs at scale (often per event or per profile), limited customisability of identity resolution, and dependence on their infrastructure for sensitive customer data. A custom CDP fits your data model, your compliance requirements and your existing stack precisely, and scales on your own terms. It is an investment that makes sense once your data volumes grow, your compliance requirements are specific, or your use cases diverge from what a standard tool offers.
How do you ensure GDPR compliance in the CDP? +
GDPR compliance is not a layer added afterwards but a design principle. We build consent management into the core of the data model: every profile carries its consent status, data minimisation determines which fields are stored, and retention rules are enforced through automated processes. Data subject rights (access, correction, erasure) are supported by technical APIs that your customer service team or self-service portal can call. Data processing agreements and data residency in the Netherlands or the EU are standard parts of the architecture. See also our information security policy.
Which systems can a CDP be integrated with? +
A CDP is by nature an integration layer. Typical sources include: website analytics (via a JavaScript SDK), mobile apps (via a mobile SDK), CRM systems, email platforms, e-commerce back-ends, till and POS systems, customer service tools and offline data sources via batch import. Typical destinations include: email platforms (Mailchimp, Klaviyo, Salesforce Marketing Cloud), advertising platforms (Google Ads, Meta), personalisation engines, analytics tools and data warehouses. The specific integrations depend on your existing martech stack. See also our API integration services.
What determines the cost of a custom CDP? +
The main factors are: the number of data sources and the quality of that data, the complexity of identity resolution (how difficult it is to recognise a customer across channels), the desired real-time processing speed, the number of downstream activation channels, and the compliance requirements. An MVP with core functionality requires a different investment than a fully developed platform with real-time streaming and multiple activation channels. After a discovery session, we prepare a clear proposal with phasing, so you can start with the core and expand when it becomes relevant. Get in touch for a no-obligation conversation.
How long does it take to build a customer data platform? +
An MVP with the core functionality — data ingestion from the key sources, unified profiles and one or two activation channels — is typically achievable in two to four months. A fully developed platform with real-time streaming, advanced segmentation, multiple integrations and a self-service audience builder takes longer, depending on the complexity of your data sources and your organisation. We work iteratively: after the first sprint you already have a working foundation with which you can begin testing and validating.

Ready to unify your customer data?

Start with a no-obligation conversation about your data challenge. We will analyse your current data sources, your activation goals and your compliance requirements, and give you a clear picture of what a custom CDP could mean for your organisation. Explore our services, read about our approach, or get in touch directly.

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✓ No-obligation introductory call • ✓ Privacy by design • ✓ No vendor lock-in • ✓ Data hosted in the Netherlands / EU

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