---
title: Markin + Amazon Redshift
url: https://markin.ai/integrations/redshift
category: Warehouses and lakes
description: Connect Markin to Amazon Redshift: read customer and revenue history in place, and write decisions and holdout assignments back.
---

# Markin + Amazon Redshift

> Direct reads against the warehouse you already operate.

**Job:** Start decisioning on Redshift with a read role and one new schema.

A Markin and Amazon Redshift setup is a read role plus a schema Markin can write to. It reads customer and revenue tables in place, decides what each customer should be offered next, and writes decisions and holdout assignments back for your existing activation pipeline to move.

No migration is required for Markin to start. The connection is a read role plus a schema it can write to, which is a change your data team can review in an afternoon.

## What can you ask Markin to do in Amazon Redshift?

- How do I add customer decisioning on top of Redshift?
- Do I need to migrate off Redshift to run next best action?
- How do I get retention actions out of Redshift and into email?
- What permissions does a decision layer need on Redshift?

## What Markin does in Amazon Redshift

- Read customer, revenue and exposure history in place.
- Build the ARPU baseline per cohort and market.
- Rank revenue opportunities by expected value and confidence.
- Write decision tables to a schema you own.
- Write holdout membership for every launched action.
- Write experiment reads joinable to your existing reporting.
- Run on your cluster inside your existing cost controls.
- Leave the warehouse exactly as it was if the connection is removed.

## The growth work behind Amazon Redshift

### Read the estate

- Map every customer, account, subscription and plan in the systems you already run.
- Rebuild the revenue baseline from orders, payments, refunds and credits.

### Find where revenue is leaking

- Size every finding in revenue, not in percentage points.
- Watch ARPU by cohort, plan, market, channel and tenure for drift that clears noise.

### Explain why

- Show the counter-evidence, not only the supporting cut.
- Keep the query trail so an analyst can reproduce every number.

### Write hypotheses worth funding

- Keep the full portfolio visible, including what was deliberately not funded.
- Write hypotheses continuously across marketing, product, pricing and technical health.

### Decide per customer

- Pick the channel, timing and incentive level, not only the message.
- Cap discount and margin exposure at the level finance agreed.

### Execute in the tools you already run

- Route offers, retention plays and save flows to the right surface.
- Open the work as a draft for approval where a human should sign off.

### Prove it caused the revenue

- Hold back a randomised control group on every decision, not one global holdout.
- Read uplift in revenue per customer against that control.

### Retire, govern and hand over

- Keep personal data in your systems and act on it in place.
- Show the whole decision trail when legal, finance or an auditor asks.

Full catalogue: [Everything a growth team does, running every day.](https://markin.ai/growth-work)

## Activation patterns

- **Attribute write-back.** Markin writes the decision onto the customer profile; your existing journeys read it as an entry condition. Latency is the platform's sync interval.
- **Read only.** Markin reads signal from this system. Nothing is written back and no schema is changed.

## What Markin reads from Amazon Redshift

- Customer and revenue tables
- Event and exposure history

## What Markin writes back

- Decision tables
- Experiment and holdout reads

## Used together with

- [hightouch](https://markin.ai/integrations/hightouch)
- [census](https://markin.ai/integrations/census)
- [braze](https://markin.ai/integrations/braze)
- [segment](https://markin.ai/integrations/segment)
- [stripe](https://markin.ai/integrations/stripe)
- [zendesk](https://markin.ai/integrations/zendesk)

## Related

- [Solution: revenue-expansion](https://markin.ai/solutions/revenue-expansion)

## FAQ

**How does Markin connect to Amazon Redshift?**

Attribute write-back, Read only. Markin writes the decision onto the customer profile; your existing journeys read it as an entry condition. Latency is the platform's sync interval.

**What does Markin read from Amazon Redshift?**

Customer and revenue tables; Event and exposure history.

**What does Markin write back into Amazon Redshift?**

Decision tables Experiment and holdout reads

**Do we have to move our data to Markin?**

No. Markin reads from your warehouse, product events and operational systems in place, on your compute, under the access rules your data team already set. Nothing is copied into a separate customer base and there is no vendor-side profile store to migrate off later.

**Does Markin replace our engagement platform or CDP?**

No, and it should not. Your engagement platform keeps the channel, the templates, the deliverability and the governance. Your CDP keeps identity and consent. Markin adds the layer neither has: deciding which action deserves to exist for each customer, and proving it against a holdout.

**What if the system we use is not listed?**

The four activation patterns cover almost everything: attribute write-back, triggered event, decision API and direct surface rendering. Any system that exposes an API, accepts a table, or can read a warehouse column can receive decisions. New connectors are built during deployment, typically in days.

Source: https://markin.ai/integrations/redshift