Digital experience glossary

This glossary defines the platform and architecture terms that come up in digital experience projects — what each system actually does, where it overlaps with its neighbours, and when it is the right choice rather than the obvious one.

We build on every major platform in these categories, so the definitions here compare categories, not vendors. Where a platform is named, it is named as an example of a category, not as a recommendation.

Twenty terms, grouped by the part of the stack they belong to rather than alphabetically — so the list reads as a map of the area instead of an index.

Foundations

• Digital transformation — putting digital technology through every part of a business, changing how it operates rather than adding tools to what already exists.
• Artificial intelligence — systems that learn from data to do work that used to need a person: reading text, recognising images, deciding what happens next.
• Cloud computing — servers, storage and software delivered on demand from a provider's data centres, so capacity is rented rather than owned.

Content, search and experience

• Digital Experience Platform (DXP) — one suite for content management, personalisation, analytics and marketing automation across every channel.
• Headless CMS — content storage decoupled from presentation, exposed through APIs so one repository can serve web, app and machine interfaces.
• Agentic CMS — a content system where AI agents curate, generate and publish against real-time context, instead of a person acting at every step.
• Content Migration — moving content and assets off a legacy system without losing structure, history or the relationships between them.
• Enterprise search — one index across the systems a company already runs, so an answer can be found without knowing which system holds it.
• User experience design — designing an interaction from research and accessibility outwards, so the interface follows how people decide rather than how the system is built.

Product and asset data

• Product Information Management (PIM) — one governed source of product data, distributed to every sales channel so descriptions and specifications stay consistent.
• Digital Asset Management (DAM) — a central library for images, video and documents, so teams find and reuse approved assets instead of recreating them.

Customer and revenue systems

• Customer relationship management — the discipline of managing every interaction with a customer from one record, so sales, service and marketing work from the same history.
• CRM Implementation — deploying that system as people, process and technology together, not as an installation.
• Customer engagement — the practice of holding a relationship over time through personalised, timely interaction rather than one-off campaigns.
• AI-Powered Dynamic Pricing — prices adjusted automatically from live demand, market and competitor signals rather than from a fixed rate card.

Back office and operations

• Enterprise resource planning — integrated software for the core of the business — finance, supply chain, people — so one set of numbers serves every department.
• Workflow Automation — business processes executed by software in predefined steps, replacing manual handoffs that drift and get skipped.

Architecture and delivery

• Composable Architecture (MACH) — systems assembled from independent best-of-breed services that talk over APIs, so one part can change without the rest.
• System integration — connecting separate applications, databases and devices so they behave as one system and data moves without being re-entered.
• Software quality assurance — testing for reliability, security and performance across the whole product lifecycle, not as a gate before release.

How these terms map to what we do

Most of these categories meet in the same project: a DXP needs product data from a PIM and assets from a DAM, and none of it holds together without integration work. Choosing between them is an architecture question, which is where digital strategy and architecture starts.

On the delivery side that becomes content operations for the editorial workflow, product data (PIM) for the catalogue, integration services for the connections between systems, and quality assurance architecture so reliability is designed in rather than tested for at the end.

On the customer side, CRM and customer engagement platforms hold the relationship, AI & data is where the automation and pricing models live, and experience design decides whether any of it is usable. Enterprise search, cloud applications and ERP by SAP cover the rest of the stack.

We implement these categories on Sitecore, Kontent.ai, Kentico, Optimizely, Adobe, Inriver, Salesforce and SAP — see the full list of technologies we work with, or the industries where these problems look different.