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RFP Package · Enterprise Applications

Digital Asset Management (DAM) RFP questions and template

122 questions, 10 demo scenarios and a five-vendor scorecard for choosing Digital Asset Management (DAM) software, in one Excel workbook.

Buy the workbook, from $499Read sample questions

What this package is for

Use it to run a Digital Asset Management (DAM) software selection, from the first long list to the final scorecard.

What the category covers. Questions for buyers of digital asset management software: metadata and taxonomy, AI tagging, search, rights and releases, brand portals, creative workflow, channel activation, renditions, video, generative AI, migration and usage analytics. Each question says what a strong answer looks like and how to check it in a demo, a sandbox or a test on the buyer's own assets.

A selection usually runs in three rounds. The package has questions for each:

  • RFI, to the long list. 25 questions screen out products that lack something you need.
  • RFP, to the shortlist. 64 questions ask how each product does the work.
  • Deep dive, to the finalists. 33 questions ask for proof on your own data.

10 demo scenarios tell each vendor what to load and what to show, so every product does the same work in front of you. 90 due-diligence questions cover security, integration, implementation and exit. The scorecard weights the answers and ranks up to five vendors.

Each question comes with why it matters, what a good answer looks like and the red flags, so the people scoring the replies know what to look for.

3 questions from the package

From the RFI round. The first shows part of the guide each question carries; the workbook adds follow-ups, how to verify the answer, a priority and a weight.

1. Can an administrator define a separate metadata schema for each asset type, such as product photography, video and brand logos, with a different set of fields on each?

Why it matters. With a single global schema, every asset shows every field. Users skip fields that do not apply to the asset in front of them, and metadata quality drops across the library.

Good answer
  • Demo shows two asset types with different field sets on the asset record
  • Asset type can be set automatically at upload by rule, such as file format or upload location
  • Fields support typed data such as date, number, controlled list and free text, not only text
Red flags
  • One global field list, with unused fields hidden only by user habit
  • Per-type schemas require custom development or a professional-services engagement
  • Asset types are simulated with folders rather than defined in the metadata model

2. For each of these enrichment types, state whether your product runs it natively, through a partner service, or not at all: keyword tagging, object recognition, scene recognition, face recognition, logo recognition, OCR on images and documents, and speech-to-text on video and audio.

Why it matters. If an enrichment type is missing or depends on an outside service, the buyer's search plan and integration scope change after selection. Partner services can also send asset content outside the platform.

3. For each of these search modes, state whether your product supports it natively, through a partner service, or not at all: keyword search, faceted search, visual-similarity search, natural-language search, search of speech in video and audio, and search of text inside documents.

Why it matters. A search mode that depends on a partner service can carry separate cost, separate indexing delays and separate permission handling. A mode the product lacks forces users back to file names and folders.

Capability areas

Metadata Model & Taxonomy (10)

Covers configurable metadata schemas per asset type, controlled vocabularies and hierarchical taxonomies, multilingual metadata values, field inheritance, conditional and required fields, bulk metadata editing, and admin changes to the model without engineering work. Excludes AI-generated tags (TAG) and search behavior (SRC).

AI Tagging & Enrichment (10)

Covers automated keyword, object, scene, face and logo recognition, OCR and speech-to-text on assets, confidence scores, custom-trained tag models, mapping AI output into the controlled taxonomy, and the human review path for low-confidence tags. Excludes generic model governance and bias testing, which the AI cross-cutting modules cover.

Search & Discovery (10)

Covers keyword, faceted, visual-similarity and natural-language search, search inside video and documents, duplicate and near-duplicate detection, saved searches and collections, and result relevance at library scale. Excludes metadata model design (MET).

Rights, Licensing & Releases (12)

Covers recording license terms per asset (channel, territory, term, usage limits), embargo dates, expiration enforcement at download and share, model and property release management, linking contracts to assets, and the notifications and takedown steps when rights lapse. Owns the rights rule and its enforcement inside the DAM; how a lapse or replacement reaches assets already published elsewhere is CHN. Excludes contract terms between the buyer and the vendor (legal-contracting-ip module).

Brand Governance & Portals (10)

Covers branded internal and external portals, guest and agency access, asset-level permissions inherited from folders, collections or metadata values, brand guideline publishing, approval-status gating, watermarking, download-format restrictions, and template-based on-brand asset creation. Excludes the review workflow for work in progress (CRE) and generic SSO and role administration (security module).

Creative Workflow, Versioning & Review (11)

Covers native plugins for desktop and browser design tools, check-out and check-in, version history and version comparison, linked-file and package handling, review-and-approve with annotation and proofing, and auto-ingest of finished work from creative tools. Excludes enterprise work-management features unrelated to assets.

Channel & Content-System Activation (10)

Covers DAM-specific connectors and behavior for CMS/DXP, PIM and e-commerce (asset-to-product linking), marketing automation, social and ad platforms, and how asset updates, replacements, rights lapses and withdrawals propagate to the places an asset is already used. Excludes the generic API, webhook and SSO surface (integration module).

Renditions, Transformation & Delivery (10)

Covers rendition presets per channel, smart and focal-point cropping, format and color-profile conversion, URL-based on-the-fly transformation, image CDN delivery and cache invalidation, and responsive variant generation without a designer. Excludes video transcoding and streaming (VID).

Video & Rich Media (9)

Covers upload and handling of large video files, transcoding profiles, adaptive streaming and preview, frame-accurate review, captions and subtitle tracks, clipping and thumbnail selection, and support for audio, 3D and layered design files. Excludes generic storage and hosting architecture (deployment-hosting module).

Generative AI & Content Supply Chain (10)

Covers generative variation, expansion and background removal inside the DAM, brand-trained generation, labeling and metadata for AI-generated or AI-edited assets, restriction of generative inputs to rights-cleared assets, and exposure of governed assets to AI agents and downstream generative tools. Excludes vendor-wide AI safety, bias and agent-permission controls (AI cross-cutting modules).

Ingestion & Library Migration (11)

Covers bulk and watched-folder ingestion, embedded metadata extraction and write-back, metadata mapping and cleanup on import, migration from legacy drives and DAMs that preserves version history, rights and relationships, and reconciliation reports. Excludes data export when leaving the vendor (migration-exit module).

Usage Analytics & Asset Audit Trail (9)

Covers tracking of views, downloads, shares and embeds per asset and user, where assets are published downstream, asset-performance data returned from channels, reuse and unused-asset reporting, asset lifecycle (archive, retention and deletion rules for assets), and an audit trail showing who used which asset, where and under which rights. Excludes system-level security logging (security module).

Demo scenarios

Each scenario lists the data to load before the demo, then the steps to show, and the questions it scores.

  1. Cleaning up and searching our legacy library
  2. An image license expires after publishing
  3. A designer revises an approved image in use
  4. Campaign renditions from one master image
  5. Time-limited portal access for an outside agency
  6. Swapping a hero image on a product page
  7. Preparing a long video for review and reuse
  8. Generating brand variants from cleared assets only
  9. Reporting on asset use after a campaign
  10. A local ad from a locked brand template

Due diligence

The workbook carries the screening questions from these modules. Each module is also sold on its own.

Questions about this package

How many Digital Asset Management (DAM) RFP questions are there?

122 solution questions in 12 capability areas: 25 for the RFI, 64 for the RFP and 33 deep-dive questions for the finalists. The workbook adds 90 due-diligence questions on security, integration, implementation and exit.

What comes with each question?

Why it matters, good-answer signals, red flags, follow-up questions, how to verify the answer (a demo step, a test or a document), and a suggested priority and weight for scoring.

Can I edit the questions?

Yes. The workbook is an ordinary Excel file. Change, add or remove questions, and change the weights; the scorecard recalculates.

Which license do I need?

The Enterprise License covers any number of evaluations inside one organization. The Consultancy License covers use with any number of clients. Neither allows reselling or republishing the questions.

Before you shortlist

The buyer guide compares the products in this category and what decides between them.

Buyer Guide
Digital Asset Management (DAM)