Customer data split across CRM, email platform, analytics, and ecommerce with no single customer record -- marketing sending campaigns to churned customers because the systems don't sync?
Segment audiences taking days of data team work for every campaign because there's no self-service segmentation tool for the marketing team?
Customer Data Platform Development
One customer record assembled from your CRM, email platform, ecommerce data, and web analytics -- so marketing segments audiences from real data and activates to the right channels without a data team request for each campaign.
We build custom CDPs for MarTech companies building data infrastructure as a product and for businesses that need a unified customer record their marketing tools can actually use.
Identity resolution and unified customer profiles
Real-time event ingestion from web, mobile, and backend
Self-service audience segmentation and activation
Data warehouse and downstream tool sync
A customer data platform (CDP) resolves customer identity across data sources, builds a unified profile from behavioural, transactional, and CRM data, and makes that profile available to marketing tools for segmentation and activation. RaftLabs builds custom CDPs for MarTech companies that need a data product and for businesses that have outgrown point solutions. Most CDP builds deliver in 14 to 18 weeks at a fixed cost.
100+Products shipped
·24+Industries served
·FixedCost delivery
·12-14Week delivery cycles
Disconnected data is not a reporting problem -- it is an operations problem
When customer data lives in separate systems with no shared identifier, every marketing operation that requires cross-system data becomes a manual process. Churn suppression requires an export from the ecommerce system, a lookup against the email platform, and a manual list upload. Personalisation requires a data analyst to join tables before the campaign team can brief the creative. By the time the data is ready, the moment for the campaign has passed.
A customer data platform makes the unified customer record a live operational asset, not a report that gets built on request. Identity is resolved continuously as new events arrive. The unified profile is updated in real time. Segment membership changes as behaviour changes, not when someone runs a query.
We build CDPs for two audiences: MarTech companies that need a data product at the centre of their platform, and businesses with enough data complexity that assembling it manually is blocking marketing operations.
What we build
Data ingestion and identity resolution
Event streams from web (JavaScript SDK), mobile (iOS and Android SDK), and server-side sources ingested in real time. Deterministic identity matching on known identifiers -- email address, phone number, customer ID -- and probabilistic matching on device fingerprints and behavioural patterns for anonymous sessions. Cross-device identity stitching that merges anonymous pre-login history with the known customer record at the point of identification. Identity graph maintained continuously as new events and identifiers arrive, so the unified profile is always current without a nightly batch job.
Unified customer profile
Single profile record for each resolved customer aggregating behavioural events, transactional history, CRM attributes, and computed properties. Full event history retained and queryable. Computed attributes updated continuously -- total lifetime spend, days since last purchase, product category affinity, engagement score. Profile schema designed around your data model rather than a fixed schema that requires your data to conform to the platform's structure. Profile API for real-time lookup by any downstream system that needs to read customer attributes.
Audience segmentation
Drag-and-drop segment builder that lets marketing teams define audiences from any profile attribute or behavioural event without writing SQL. Conditions including event frequency, recency, attribute ranges, and computed property thresholds. Real-time segment membership for contacts that meet entry conditions as they occur, and scheduled refresh for segments that run on a cron basis. Segment size estimates shown before the segment is saved so the team knows the audience size before building a campaign around it.
Activation and downstream sync
Push audience segments to Meta Custom Audiences, Google Customer Match, and TikTok Custom Audiences in real time as segment membership changes. Sync segments to email platforms -- Klaviyo, Mailchimp, Braze -- and to your CRM for sales outreach. Webhook delivery for activation to custom downstream systems. Activation log showing when each contact was added to or removed from an audience in each destination. The sync layer that means segment membership in your CDP is immediately reflected in your ad platforms and outreach tools without a manual export step.
Event pipeline and data quality
Schema validation on ingest to catch malformed events before they corrupt the unified profile. Deduplication of duplicate events from retry logic or client-side double-fires. PII detection and masking for fields that should not be stored in plain text. Data lineage tracking so every profile attribute is traceable to a source event. Schema evolution management so adding new event types or properties does not require downtime or manual migration. The data quality infrastructure that makes downstream analytics and activation reliable.
Analytics and reporting
Segment size trends over time to track audience growth and decay. Profile coverage metrics showing what percentage of profiles have data from each source, so gaps in the identity graph are visible. Activation performance by destination -- match rates for ad platform uploads, email deliverability by segment. LTV distribution by segment to identify which audience definitions correlate with high-value customers. Reporting designed for the marketing team to understand their data, not for data analysts to diagnose infrastructure.
Frequently asked questions
A CDP is a system that collects customer data from multiple sources, resolves identity across those sources, and makes a unified customer profile available to marketing and analytics tools. You need one when the absence of a unified customer record is causing operational problems: campaigns sent to the wrong audience because systems don't sync, personalisation that requires a data analyst for each execution, or reporting that requires manual joins from multiple exports. If your marketing team can segment and activate audiences from your current stack without a data team request, a CDP is not your priority. If they can't, it probably is.
Identity resolution combines deterministic and probabilistic matching. Deterministic matching links records that share a known identifier -- the same email address, phone number, or customer ID. When an anonymous user on a new device logs in, their pre-login event history is stitched to their known profile using the deterministic match on the login identifier. Probabilistic matching uses device fingerprints, behavioural patterns, and IP data to link anonymous sessions that are likely the same person but have no shared identifier. The identity graph is updated continuously as new events arrive, so a customer who uses three devices and two email addresses ends up as one profile with the full history from all sessions.
Standard activation destinations include Meta Custom Audiences, Google Customer Match, TikTok Custom Audiences, LinkedIn Matched Audiences, and Snapchat Customer Lists for paid media. For email and CRM, we build sync to Klaviyo, Mailchimp, Braze, Salesforce, and HubSpot. For custom destinations, we provide a webhook delivery mechanism so any system with an API can receive segment membership updates. Activation is real time for event-triggered segments -- a customer who completes a purchase is removed from a win-back segment and added to a post-purchase segment within seconds, not on a nightly batch schedule.
A CRM is a sales tool that tracks customer relationships and pipeline -- it is designed for sales team workflows, not for real-time marketing activation. A data warehouse stores historical data for analytical queries -- it is designed for reporting, not for powering real-time personalisation or ad audience sync. A CDP sits between them: it ingests data from both, resolves identity at the customer level, and makes that resolved profile available to marketing tools in real time. The CDP does not replace the CRM or data warehouse -- it reads from them and makes the combined data operational for marketing use cases that neither tool handles well on its own.
