Drop clean marketing data in Amazon S3 — query-ready
Forward a normalized marketing data lake to S3 in your AWS account. Parquet by default, partitioned by date and source, ready for Athena, Glue, EMR, or anything downstream.
Amazon S3 is the default data lake for AWS-native data teams. It's where event-level data, archives, and warehouse staging live before they're queried by Athena, Redshift Spectrum, or processed by Glue and EMR. Cheap, durable, infinitely scalable.
Building a marketing data lake means engineering each platform's API, formatting the output as Parquet or JSON, partitioning sensibly, and keeping it all alive when an API ships a new version. Clarisights does that work upstream and writes the result straight to a bucket you control — partitioned, compressed, and ready for Athena to query on day one.
Datasets Clarisights writes to S3
From CMO-level summaries to weekly business reviews — every chart pulls from the same Clarisights feed.
Unified Spend Dataset
s3://marketing-lake/unified_spend/ — Channel-agnostic spend, conversions, and impressions — Parquet, daily-partitioned, ready for Athena and Glue.
Creative Performance Dataset
s3://marketing-lake/creative_performance/ — Creative-level performance preserving platform-native dimensions, with unified metrics layered on top.
Blended Attribution Dataset
s3://marketing-lake/attribution_blended/ — MMP and last-click data joined to spend — refreshed hourly into a partitioned table the warehouse can stage from.
Build a marketing data lake, or get one delivered
Most teams need a marketing data lake but underestimate what it takes to build and maintain one. Clarisights ships a managed alternative — landed in your bucket, partitioned for Athena, refreshed on schedule.
Build it yourself
Three to six months of API engineering, format conversion, and partitioning logic
API schema changes break your jobs silently — and your Athena queries with them
Backfills, retries, and DLQs become a permanent on-call burden
Every new channel = another extractor, another partition strategy, another runbook
Connect these sources to Looker Studio
Your most-used ad platforms, attribution tools, and revenue systems — unified into one feed and ready for any chart.
How teams use Looker Studio with Clarisights
Three patterns we see across the customer base. Each one starts in Clarisights and lands in a Looker Studio dashboard the team actually checks.
E-commerce & DTC
• Land marketing data in S3 alongside transaction logs, web events, and CDP exports • Stage into Redshift, Snowflake, or Iceberg tables — the same lake feeds every warehouse downstream • Run Athena over a unified marketing prefix without standing up a warehouse first
Gaming & Apps
• Combine MMP data, SKAN postbacks, and paid spend in one S3-backed marketing lake • Power EMR/Spark cohort and LTV models with stable, partitioned input data • Feed feature stores with marketing inputs that don't break when an API changes
B2B SaaS
• Keep marketing data in your own AWS account, under your governance and retention rules • Stage into governed warehouse tables only after audit and lineage checks • Power BI, ML, and finance workloads from a single AWS-native source of truth
Going live in Looker Studio
Three steps. No data-engineering project. Most teams query their first unified marketing prefix the same day.
STEP 1
Connect your sources to Clarisights
Authorize each ad platform once. Clarisights handles schema unification, retries, and historical backfill upstream.
STEP 2
Point Clarisights at an S3 bucket you own
Grant a cross-account IAM role write access to a bucket and prefix you control. Clarisights starts writing partitioned Parquet immediately.
STEP 3
Query, stage, and process — without owning the pipes
Athena, Glue, EMR, and warehouse copy jobs all read the lake directly. Schemas stay stable across platform API changes.
Already piping data into Looker Studio with another tool?
Already running custom S3 ingestion jobs for marketing data?
Those tools are pipes — they shuttle data into Looker Studio and stop there. Clarisights ships the same pipe, then layers on normalization, calculated metrics, monitoring, and the reporting interface your team won't outgrow in six months.
Frequently Asked Questions
Connect in minutes. Your first cross-channel dashboard is ready the same day. No engineering required.
