We map your customer journeys, then architect the event tracking and attribute layer that powers your entire lifecycle stack — so your automations trigger on real behaviour, your AI has clean data to learn from, and personalisation actually works at scale.
Our engineering and strategy team starts with your customer journey, designs the event taxonomy to match, and implements everything end-to-end — giving your AI and campaigns the data backbone they need.
We map your full customer journey — from first touch to post-purchase and beyond — then work with your product and marketing teams to identify every event, attribute, and data point your lifecycle campaigns need to deliver real personalisation.
We create a structured, scalable event naming convention and attribute schema anchored to your journey map keeping data clean, queryable, and ready for AI-driven segmentation and campaign logic.
Our engineers implement event tracking via your CDP, data warehouse, or marketing platform API — connected to your product and transactional data so your AI models and campaigns work off a single source of truth.
We run end-to-end testing to confirm every event fires correctly, attributes populate in real-time, and your campaign triggers work exactly as designed because bad data is worse than no data.
You get a living data dictionary and event catalog. As your product evolves, we update your tracking layer so your marketing data, AI models, and personalisation never fall out of sync.
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An event taxonomy is a structured naming system for every user action your platform tracks — things like ‘product_viewed’, ‘checkout_started’, or ‘subscription_upgraded’. It matters because without a clean, consistent taxonomy, your AI models can’t learn properly, your campaign triggers misfire, and your personalisation falls apart. It’s the data backbone that everything else runs on.
It depends on the complexity of your product and current data infrastructure. For most brands, we complete the full journey mapping, schema design, implementation, and QA within 4–8 weeks. Simpler setups can be live in as little as two weeks.
Minimal involvement. Our engineers handle the implementation directly via your CDP, data warehouse, or marketing platform API. We typically need a few sessions with your product and engineering teams for discovery and access provisioning, but the heavy lifting is on us.
We work with all major CDPs and data infrastructure including Segment, mParticle, Rudderstack, and native platform APIs for Braze, Customer.io, MoEngage, CleverTap, and more. We also integrate with data warehouses like BigQuery, Snowflake, and Redshift.
That’s exactly why we provide a living data dictionary and event catalog. When your product evolves, we update the tracking layer, add new events, and ensure your segmentation, campaign triggers, and AI models stay in sync. This can be part of an ongoing management engagement or handled on a project basis.
We run end-to-end validation and QA before anything goes live confirming every event fires correctly, attributes populate in real-time, and triggers work as designed. Post-launch, we monitor data quality and flag anomalies.
