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Marketing data pipelines that actually run in production.

Most marketing data problems aren't analytics problems. They're pipeline problems. Bad connectors. Schema drift. No normalization layer. Data that arrives late, arrives wrong, or doesn't arrive at all.

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The three failure modes every marketing pipeline hits.

These aren't edge cases. They're Tuesday morning at 8am.

Connector rot

Platform APIs change. Your connector breaks at 2am. Nobody notices until the Monday report is wrong.

Schema drift

Google Ads adds a field. Your pipeline silently drops it. Your attribution model is now wrong by an unknown amount.

No normalization

Every platform defines "click" differently. You have 8 sources of truth and none of them agree.


Infrastructure that holds up under real load.

Everything we build is monitored, alertable, and designed for the failure modes we've already seen.

01
Ingestion pipelines
Airbyte-based or custom connectors for ad platforms, CRMs, and marketing tools. Reliable, monitored, alertable.
02
Real-time event streams
Kafka-based pipelines for campaign events, conversion signals, and audience updates that can't wait for a nightly batch.
03
Redis caching layer
Fast-access layers for dashboards and reporting APIs that need sub-second response without hammering the warehouse.
04
Normalization & deduplication
Cross-platform entity resolution. One customer record. One campaign record. Regardless of how many platforms claim ownership.

The tools we build on.

AirbyteKafkaRedisPythonPostgresBigQuerySnowflakeDatabricksdbtAirflow

At TapClicks I built and maintained 200+ data connectors serving thousands of marketing agencies — ingesting billions of campaign events across Google, Meta, TikTok, and 200 other platforms. I've seen every failure mode a marketing data pipeline can have.

AR
Angshuman Rudra
Founding PM, TapClicks · 10 years

Start with a Data Architecture Review.

Two hours. We map your current pipeline, find the failure points, and give you a prioritized fix list. $2,000 flat.

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