MarTech Acronym Decoder

The system of record for known customers and accounts: contacts, deals, service history, and sales activity.

When it applies

Whenever you need an authoritative record of relationships, especially in sales-led and B2B contexts.

Often confused with

CDP. A CRM holds known, sales-oriented records; a CDP unifies all first-party behaviour into marketing-ready profiles.

A system that unifies first-party data into persistent, governed customer profiles and makes them available to other tools.

When it applies

When data is siloed across sources and you need one trusted profile to power personalisation and segmentation.

Often confused with

DMP (anonymous, cookie-based, ad-focused) and CEP (which acts on profiles rather than just building them).

A CDP that ingests, computes, and activates profiles in real time rather than on a batch rebuild cycle.

When it applies

When personalisation depends on signals that are seconds old, not hours old.

Often confused with

A standard CDP. The label is sometimes positioning more than a hard guarantee, so probe the latency claims.

A CDP assembled from your own warehouse plus best-of-breed components, rather than a single packaged product.

When it applies

When the data warehouse is already the source of truth and you want to avoid duplicating it into a packaged CDP.

Often confused with

A packaged CDP. Composable keeps data in the warehouse and adds modelling and activation on top.

An older, largely anonymous store built around third-party cookies and audience segments for advertising.

When it applies

Paid-media audience targeting, though its relevance has faded with third-party cookie deprecation.

Often confused with

CDP, which is first-party, identity-rich, and persistent rather than anonymous and short-lived.

A loosely used term for a data layer aimed at marketing analytics and activation, often warehouse-centric.

When it applies

When the conversation is about marketing data modelling and activation rather than a packaged profile store.

Often confused with

CDP. The boundary is genuinely blurry, which is exactly why the term gets contested.

A cloud analytical database (Snowflake, BigQuery, Databricks, Redshift) increasingly used as the source of truth for customer data.

When it applies

When you want one governed place to model data that both analytics and activation can draw from.

Often confused with

A CDP. A warehouse stores and models data; a CDP packages identity, profiles, and activation around it.

Pipelines that move data between systems. ELT loads first and transforms inside the warehouse; ETL transforms before loading.

When it applies

Any time data has to move from source systems into a warehouse or platform.

Often confused with

Reverse ETL, which sends modelled data the other way, out to operational tools.

Syncing modelled data from the warehouse back out into operational tools such as the CEP, ad platforms, or CRM.

When it applies

When the warehouse holds your best audiences and traits and you need them activated in marketing tools.

Often confused with

Zero-copy, which aims to query data in place rather than copy it out at all.

A pattern where engagement tools query data in the warehouse directly instead of copying it into their own store.

When it applies

When the warehouse is the source of truth and you want to avoid duplicating governed data.

Often confused with

Reverse ETL, which still moves data out. Zero-copy aims to act on it in place.

A platform that decides and executes cross-channel engagement: orchestration, messaging, and increasingly real-time decisioning.

When it applies

When the problem is acting on data across channels, not just storing it.

Often confused with

CDP (which unifies data) and MAP (which automates mostly email and lead flows).

Tooling for automating campaigns, lead nurturing, and scoring, historically email-first and often B2B.

When it applies

Lead lifecycle, nurture flows, and sales handoff in considered-purchase contexts.

Often confused with

CEP, which is broader, more real-time, and channel-agnostic.

A platform focused on sending email at scale with the deliverability infrastructure behind it.

When it applies

When email is the channel and deliverability is the core concern.

Often confused with

MAP and CEP, which include email but add automation, multi-channel, and decisioning.

An analyst category (notably Gartner) for platforms that orchestrate marketing across channels from a central hub.

When it applies

When evaluating enterprise platforms against an analyst frame.

Often confused with

CEP. The categories overlap heavily; MMH is the analyst label, CEP the more common market term.

A decisioning pattern where a system selects the most valuable action for a customer at a given moment.

When it applies

When you have competing offers and journeys and need a principled way to choose between them.

Often confused with

A campaign. NBA is a decisioning approach, not a channel or a one-off send.

AI systems that can plan and take multi-step actions toward a goal with limited human input, not just generate content or predictions.

When it applies

When moving from rule-based automation toward autonomous, goal-driven engagement, within clear guardrails.

Often confused with

Generative AI (which produces content) and classic automation (fixed rules). Agentic AI decides and acts across steps.

Manages how customers register, authenticate, and consent, and links those known identities to their profiles.

When it applies

When logged-in experiences, account security, and known-identity linkage matter.

Often confused with

Identity resolution inside a CDP, which stitches behaviour into a profile rather than handling authentication.

Tooling that captures, stores, and enforces user consent and preferences across systems.

When it applies

Any stack handling personal data under GDPR, ePrivacy, or similar regimes.

Often confused with

Preference centres, which are a feature, not the governance and propagation layer a CMP provides.

A privacy-preserving environment where two parties match and analyse data without either exposing raw, individual-level records.

When it applies

When collaborating on audiences or measurement with a partner or platform under strict privacy constraints.

Often confused with

A CDP. A clean room enables governed collaboration across parties; a CDP unifies your own first-party data.

A platform for building and managing digital experiences: content, web, and increasingly commerce and personalisation.

When it applies

When the owned web and content experience is the centre of gravity.

Often confused with

CMS (narrower, content only) and CEP (engagement and messaging rather than experience management).

A system for creating, managing, and publishing content, increasingly headless and API-first.

When it applies

Whenever content needs to be authored once and delivered to many surfaces.

Often confused with

DXP, which wraps a CMS in experience, personalisation, and orchestration capabilities.

A managed library for brand and creative assets: images, video, and the rights and metadata around them.

When it applies

When many teams and channels reuse approved creative and need one governed source.

Often confused with

A CMS, which manages published content; a DAM manages the raw assets that content draws on.

A single source of truth for product data: descriptions, attributes, specifications, and relationships.

When it applies

Commerce and catalogue-heavy contexts where product data feeds many channels.

Often confused with

A DAM (creative assets) and a CMS (content). PIM is specifically structured product data.

A set of principles for composable architecture: independent services, API-first integration, cloud-native delivery, and headless front ends.

When it applies

When you want to assemble best-of-breed components instead of a single monolithic suite.

Often confused with

Composable in general. MACH is a specific, stricter set of principles, not just a buzzword for modular.

Decoupling the back-end content or commerce engine from the front-end presentation, connected by APIs.

When it applies

When one content or product source must serve many front ends (web, app, kiosk, voice).

Often confused with

MACH, which includes headless as one of four principles alongside microservices and API-first.

Cloud tooling for connecting systems and moving data between them without bespoke point-to-point code.

When it applies

When the integration surface is large and you want governed, reusable connections.

Often confused with

ETL/ELT, which is data-pipeline focused, whereas iPaaS is broader application integration.

A top-down, statistical approach that estimates each channel’s contribution to outcomes using aggregate data.

When it applies

When privacy limits user-level tracking and you need a durable, channel-level view of effectiveness.

Often confused with

MTA, which is bottom-up and user-level. The two answer different questions and increasingly run together.

A bottom-up method that distributes credit across the touchpoints in a converting journey.

When it applies

When you can track journeys at user level and want to compare touchpoint contribution.

Often confused with

MMM (aggregate, privacy-durable) and last-touch attribution (simpler and usually misleading).

A server-side method of sending conversion and event data directly to ad platforms, rather than relying on the browser pixel.

When it applies

When browser-based tracking is degraded and you need durable conversion signal for ad optimisation.

Often confused with

The browser pixel, which CAPI supplements or replaces, and reverse ETL, which targets your own tools rather than ad platforms.

The ongoing erosion of user-level marketing data caused by cookie deprecation, privacy regulation, and rising opt-outs.

When it applies

As context for nearly every modern data decision: it is why first-party data, CAPI, clean rooms, and MMM are all rising.

Often confused with

Not a tool but a driver. It is the reason behind the shift to first-party data and privacy-durable measurement.

A B2B strategy that targets a defined set of high-value accounts with coordinated, personalised programmes.

When it applies

Complex B2B sales with a small number of high-value accounts and long buying committees.

Often confused with

Lead-based demand generation, which optimises volume of individuals rather than depth on named accounts.

A richer successor to SMS supporting branded sender identity, media, and interactive elements in the native messaging app.

When it applies

When mobile messaging needs more than plain text and you want a verified brand presence.

Often confused with

SMS (plain text) and in-app messaging (inside your own app rather than the device messenger).