---
title: Markin + Optimove: deciding what deserves a campaign at all
url: https://markin.ai/compare/markin-and-optimove
kind: stack
description: Optimove orchestrates and prioritises retention campaigns. Markin decides which revenue opportunity deserves one, sizes it, and proves it against a holdout.
updated: 2026-09-03
---

# Markin + Optimove: deciding what deserves a campaign at all

> Optimove is a retention marketing platform: customer segmentation, multichannel campaign orchestration and automated prioritisation between recurring campaigns. Markin sits before it and decides which commercial opportunity is worth acting on per customer, and what it is worth. The decision is Markin's; the campaign is still built and delivered by Optimove.

## In short

- Optimove: Which of our campaigns should this customer receive, and through which channel? Output: Delivered campaigns, prioritisation decisions and campaign-level reporting.
- Markin, the decision + execution layer: Which opportunity justifies contact for this customer, and what is it worth? Output: A ranked, sized decision per customer,  including hold, written back into Optimove.
- Automated prioritisation chooses between campaigns that already exist; nothing proposes the campaign that does not exist yet.
- Markin does not orchestrate campaigns and does not want the CRM calendar.

## What each layer is

**Optimove**, A retention and CRM marketing platform: customer modelling and segments, multichannel campaign orchestration, and automated prioritisation between the recurring campaigns a team maintains.

Answers: Which of our campaigns should this customer receive, and through which channel?

**Markin, the decision + execution layer**, A layer that generates and sizes revenue opportunities per customer, ranks them on expected incremental margin, selects a treatment and decides when not to contact at all.

Answers: Which opportunity justifies contact for this customer, and what is it worth?

## Side by side

|  | Optimove | Markin, the decision + execution layer |
| --- | --- | --- |
| Question it answers | Which of our campaigns should this customer receive, and through which channel? | Which opportunity justifies contact for this customer, and what is it worth? |
| Primary input | Customer attributes and lifecycle segments, campaign definitions, response history. | Customer context, outcomes, margins, contact history, constraints, past experiment results. |
| Primary output | Delivered campaigns, prioritisation decisions and campaign-level reporting. | A ranked, sized decision per customer,  including hold, written back into Optimove. |
| Usual owner | CRM and retention marketing. | Growth, data science and revenue leadership. |
| How it's measured | Uplift versus the campaign control group, response and retention rates. | Incremental revenue and ARPU against a randomised holdout. |

## Top alternatives to Optimove

Teams looking at Optimove alternatives are usually solving one of two different problems: they want a different orchestration platform, or they want a decision layer above the one they already run. These are the options buyers shortlist most often, and what each is actually good at.

| Alternative | What it is | Best for | Watch out |
| --- | --- | --- | --- |
| Braze | Cross-channel engagement platform with Canvas journeys and its own decisioning features. | Product-led consumer apps that want mobile-first messaging and a large partner ecosystem. | Decisions are optimised inside Braze journeys, so the choice of which opportunity to pursue stays with the team. |
| MoEngage | Insights-led engagement platform with Sherpa AI optimisation. | High-volume mobile bases in retail, fintech and media where push and in-app carry the programme. | Optimisation is channel and send-time led rather than margin led. |
| Iterable | Lifecycle marketing platform with the Nova intelligence layer. | Marketing teams that want journey building and AI assistance in one workspace. | AI outputs are designed for use inside Iterable segments and journeys. |
| Salesforce Marketing Cloud | Enterprise suite with Einstein and Agentforce on top of the CRM estate. | Organisations already standardised on Salesforce data and service workflows. | Programme weight and implementation cost are the usual constraint, not capability. |
| Markin | Agentic growth layer that generates, prices and tests revenue hypotheses above whatever you send with. | Enterprise B2C teams whose bottleneck is learning speed and ARPU, not message delivery. | Markin does not send messages. It needs an activation route, which can be Optimove itself. |

## What stays unsolved when Optimove is running well

A mature Optimove programme is rarely short of campaigns. It is short of new, sized hypotheses, and short of a way to know which of the running plays actually created revenue rather than harvested it.

- Automated prioritisation chooses between campaigns that already exist; nothing proposes the campaign that does not exist yet.
- Hypotheses outside the CRM surface,  pricing, onboarding friction, a broken payment flow, never enter the calendar at all.
- Campaign-level control groups measure a campaign, not the combined revenue effect of everything a customer received.
- Throughput is bounded by how fast the CRM team can brief, build and read campaigns.

## How the two run together

1. **Context in.** Markin reads customer context where it already lives,  warehouse, billing, product and support systems, together with Optimove campaign and response history.
2. **Decision.** Markin generates and sizes revenue opportunities, ranks them per customer on expected incremental margin, chooses a treatment and assigns a control group.
3. **Activation back into Optimove.** The chosen decision is written back as a customer attribute or event, so an existing Optimove campaign selects and delivers it. Channel governance, content and consent stay in Optimove.

## Optimove's own decisioning layer

Products: Optimove Native AI, OptiGenie, AI Decisioning Studio, AI Journey Decisioning Agent (formerly Self-Optimizing Journeys)

Optimove has a real decisioning layer for retention marketing. It prioritises between the recurring campaigns a CRM team has already built, and increasingly drafts them too. That is a different scope from generating the commercial hypothesis in the first place and sizing what it is worth.

**What it optimises**

- Optimove Native AI is presented as an agentic layer running decisioning, insights and creative agents on unified customer data, with a conversational agent built in. [Vendor page: Optimove, Native AI product page](https://www.optimove.com/platform/optimove-ai/native-ai)
- OptiGenie is documented as an AI assistant for marketers across AI Insights, AI Creation and AI Orchestration, aimed at personalisation, productivity and customer loyalty. [Vendor docs: Optimove Academy, OptiGenie](https://academy.optimove.com/hc/en-us/articles/14655206870813-OptiGenie)

**Documented constraints**

- The AI Journey Decisioning Agent is composed of the recurring campaigns whose target group is set to Auto on the prioritisation page, so its scope is the set of campaigns a human has already created inside Optimove. [Vendor docs: Optimove Academy, AI Journey Decisioning Agent FAQ](https://academy.optimove.com/hc/en-us/articles/8717576629149-AI-Journey-Decisioning-Agent-formerly-Self-Optimizing-Journeys-FAQ)
- Prioritisation and optimisation happen inside Optimove's own campaign and channel model; there is no documented arbitration against product, pricing, service or field touchpoints that Optimove does not send. [Vendor page: Optimove, Native AI product page](https://www.optimove.com/platform/optimove-ai/native-ai)

**Evidence**

- The published economic case is a Total Economic Impact™ study conducted by Forrester Consulting and commissioned by Optimove, rather than independent benchmarking of the decisioning agent. [Vendor-commissioned: Forrester TEI of Optimove, commissioned by Optimove](https://www.optimove.com/resources/ebooks/total-economic-impact-tei-of-optimove)

**Where Markin differs**

- **Generates the hypothesis, not just the winner.** Optimove ranks the campaigns you built. Markin proposes the campaigns worth building,  including pricing, onboarding and product-side actions no CRM calendar contains, and sizes each one before anyone writes it.
- **Ranked on margin, with hold as a real option.** Prioritisation is done on expected incremental revenue net of margin and contact cost, so leaving a customer alone competes with every campaign on the calendar.
- **Read against a randomised holdout.** Every decision carries a control group, so the reported number is incremental ARPU rather than response rate on the campaign that happened to win the slot.

## What Markin does not replace

To be explicit about scope, because procurement will ask:

- Markin does not replace Optimove campaign orchestration, templates or channel delivery.
- Markin does not own consent, frequency caps or channel governance.
- Markin is not a CRM or a customer database of record.
- Markin does not take over campaign reporting; it adds a holdout-based revenue read.

## Where Markin fits

Markin does not orchestrate campaigns and does not want the CRM calendar. It decides which commercial opportunity is worth pursuing per customer and returns that decision so Optimove can execute it through the campaigns and channels you already run.

- **New hypotheses, not just better prioritisation.** Opportunities are generated across marketing, product, pricing and technical health, then sized, so the calendar stops being the boundary of what can be tested.
- **One decision per customer, across the estate.** Markin arbitrates between everything a customer could receive,  an Optimove campaign, a service contact, an in-product placement, and picks one.
- **Proven against control, by default.** Nothing scales on a number that has not survived a randomised holdout read over a full measurement window.

Next: [Retention Decisioning](https://markin.ai/solutions/retention-decisioning)

## When Markin is not the right answer

- You have no reliable outcome or revenue data to read decisions against.
- Your base is small enough that the CRM team can reason about every segment by hand.
- You want a replacement for campaign orchestration rather than a decision layer above it.

## FAQ

**Doesn't Optimove already have AI decisioning?**

Yes, and it is a real one. Optimove's AI Journey Decisioning Agent prioritises between recurring campaigns whose target group is set to Auto, and OptiGenie assists with insights, creation and orchestration. That optimises the set of campaigns your team has already built inside Optimove. Markin generates the opportunity itself, sizes it in margin terms, and can act outside the CRM surface.

**Do we have to replace Optimove?**

No. Optimove keeps segmentation, orchestration, content and delivery. Markin supplies a ranked, sized decision per customer that Optimove executes.

**How does the decision reach Optimove?**

As a customer attribute carrying the chosen action and its expiry, or as an event that triggers an existing campaign. No new delivery infrastructure is introduced.

**How is a Markin holdout different from an Optimove control group?**

An Optimove control group measures one campaign against non-recipients. A Markin holdout is attached to the decision, so the number reported is the incremental revenue of choosing that action for that customer, net of everything else they received.

**What does the first ninety days look like?**

One revenue theme, one activation route into Optimove, a real holdout. The goal of the first quarter is a defensible incremental number, not coverage of the whole calendar.

**How is Markin different from the decisioning or AI already inside Optimove?**

A decisioning engine ranks actions a human already defined, inside the campaign surface it was given. Markin forms the hypotheses itself,  marketing, product, pricing or a technical anomaly holding growth back, sizes them, executes them inside Optimove and your product surfaces, and reads each one against a randomised holdout. It behaves like a data science and growth team, not like an optimiser.

**Does Markin only test messages and offers?**

No. Anything a human growth scientist would investigate is in scope: onboarding friction, feature adoption, pricing and packaging, dunning, and technical health issues such as a checkout error rate or a broken deeplink quietly killing conversion. Marketing is one of four hypothesis domains, not the boundary.

**What is the business case for adding Markin on top of Optimove?**

On the assumptions preloaded above, 3.0M customers at 22 a month, a small move in ARPU is a large number in absolute terms, because it applies to the whole installed base every month rather than to a campaign. Across Markin deployments the verified range on treated cohorts is +17% to +35% ARPU against a randomised holdout. The point is not more messages: it is finding the highest-value action per customer, launching it, and proving it against control before it scales.

**How long before it pays for itself?**

First sized opportunities are in test within six weeks and the first holdout-verified result lands inside 90 days. Payback depends on your base, margin and programme cost, the calculator on this page computes it from your own numbers, after applying the 20% to 40% haircut BCG finds when next-best-action programmes are incrementality-tested.

Source: https://markin.ai/compare/markin-and-optimove