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Composable vs. Pre-Composed DXPs in 2026: A Two-Track Evaluation Framework for Modern DXP Selection

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Composable vs. Pre-Composed DXPs in 2026: A Two-Track Evaluation Framework for Modern DXP Selection

Dan Drapeau of DXP Catalyst - headshot
Dan Drapeau
7 mins
An illustration of two sets of train tracks running side by side towards the horizon, and converging through big letters "DXP" that appear in the distance. The tracks run under the letter "X" in "DXP."

When selecting your next DXP, there are critical considerations from an architectural perspective. Whether you choose composable or pre-composed, here's an evaluation approach to help ensure that things don't go off the rails.

 

Dan Drapeau is Managing Director at DXP Catalyst Consulting and a CMS Critic contributor. 


 

Composable architecture is now firmly part of mainstream enterprise conversations. Suite vendors have become more modular, and headless platforms have expanded their native capabilities, in several cases evolving into full DXPs through acquisition. AI capabilities, including emerging agentic workflows, are embedded across most major offerings. The competitive landscape has converged across architectural models.

Evaluation approaches have not evolved at the same pace.

Many organizations still assess DXPs through a single-track process that emphasizes feature breadth, demo cohesion, and tightly integrated product narratives. That structure naturally favors pre-composed suites and can disadvantage ecosystem-driven models before architectural tradeoffs are fully examined.

This is not another debate about composable versus monolithic technology. It is a practical evaluation framework designed to ensure that platform capability and ecosystem architecture are assessed with equal rigor.

By “pre-composed,” I refer to suite-style platforms that deliver a bundled set of tightly integrated products from a single vendor. While components may be licensed independently, the underlying architecture assumes close internal coupling across core capabilities.

Evaluating composable and pre-composed approaches fairly requires structural changes to how selection and architectural review are conducted.

Why a Single Evaluation Track Creates Structural Bias

Traditional evaluations follow a single-track model: RFP issuance, vendor demos, stakeholder scorecards, and aggregate scoring. Functional breadth and demo cohesion often dominate.

That structure works when all vendors provide tightly integrated suites. It becomes problematic when some vendors operate as orchestration layers or depend on ecosystem components for search, DAM, CMP, or CDP.

In those scenarios, the evaluation model itself shapes the outcome. Vendors showcasing native breadth in a single interface frequently score higher than vendors demonstrating integration patterns, even when the latter may offer stronger long-term flexibility.

Separating platform capability from ecosystem architecture mitigates this bias.

The Two-Track Evaluation Model

A more balanced approach separates platform evaluation from ecosystem architecture by running two structured tracks in parallel:

 

Track 1. Core Platform Evaluation

The first track evaluates the DXP as a product:

  • Functional capability across CMS, personalization, experimentation, and adjacent experience services
  • Operational and governance maturity
  • Architectural alignment with existing systems
  • Non-functional readiness – including performance, security, and compliance
  • Licensing structure and cost trajectory
  • Vendor profile and strategic direction

This clarifies what adopting the platform as the core DXP means over a multi-year horizon.

 

Track 2. Ecosystem and Composability Evaluation

The second track evaluates the broader architecture independently of the platform.

Rather than asking whether a DXP bundles search, CMP, or CDP as native products, this track examines how those capabilities function within the proposed architecture and whether the DXP can realistically serve as the coordination layer for a broader ecosystem. It evaluates:

  • Data and analytics architecture, including warehouse alignment and experimentation visibility
  • Sequencing strategy across ecosystem capabilities such as CDP, personalization, and search
  • Search strategy, including conversational and LLM-driven experiences
  • AI capabilities, automation patterns, and governance controls
  • DAM and content asset strategy
  • Hosting and front-end flexibility
  • Integration maturity and connector quality

The objective is to assess not only what the platform includes today, but whether it enables durable evolution over time. Best-of-breed services should integrate without architectural strain, and new capabilities should be introduced without creating lock-in, rework, or hidden dependencies.

CDP strategy illustrates why this separation matters. Evaluation should focus on where customer data is modeled and how activation occurs within the architecture. In warehouse-centric environments, introducing a suite-coupled CDP can shift the system of record and create unnecessary duplication. Understanding whether activation depends on the DXP’s native data layer or can remain decoupled reveals how tightly the ecosystem is structured. Similar substitution questions apply across search, DAM, and AI.

Operationalizing the Two-Track Model

Separating ecosystem architecture from platform scoring ensures both models are assessed on equal footing.

In practice, this model typically unfolds over 5-7 weeks. Vendors prepare and deliver platform demonstrations while ecosystem discovery and architectural modeling occur in parallel. Weighting across both tracks should be defined before demos begin and documented explicitly, since bias can re-enter through weighting decisions even when intent is neutral.

The Complexity of Running Parallel Tracks

Parallel tracks introduce rigor and practical complications.

Differences in native coverage complicate comparison. If CMP, search, or CDP are weighted heavily but not natively provided by all vendors, those capabilities should move into the ecosystem track rather than penalizing the platform score. Foundational capabilities such as CMS remain in the platform track, while optional or externally delivered services belong in ecosystem evaluation.

Vendors may bring partners into demos to illustrate integration. That can be appropriate, but evaluation should focus on architectural feasibility, operational ownership, and governance responsibility rather than demo choreography.

When multiple DXP vendors recommend the same ecosystem component, such as a shared search or data platform, that element should be evaluated independently so that differences in governance, scalability, and integration maturity remain visible.

Without disciplined separation, weighting decisions can distort outcomes even when intent is neutral.

Synthesizing the Results

Synthesis is not about averaging scores.

Track 1 produces weighted scoring across functional, operational, architectural, and non-functional criteria. Track 2 evaluates whether the platform can realistically serve as the hub of a broader ecosystem.

For composable-oriented platforms, this means assessing how cleanly external products plug in for search, CDP, DAM, or CMP, and what governance or integration overhead that introduces. For pre-composed suites, it means pressure-testing substitution claims. If a component can be replaced, what constraints exist in practice? Does personalization depend on a native CDP? Does experimentation assume native analytics?

Review both outputs side by side and reconcile tensions. A platform may score highly in functional breadth yet limit ecosystem flexibility. A composable option may offer architectural openness while introducing additional governance responsibility.

Leadership must articulate what the organization is optimizing for: time-to-value, long-term flexibility, operational simplicity, or ecosystem optionality. Without clarity, decisions default to demo cohesion.

Sequencing also becomes part of synthesis. Organizations may defer CDP activation or advanced orchestration. The selected architecture should support phased rollout without creating integration debt or future re-platforming risk.

Shortlisting 2 vendors from an initial field of 4-5 keeps reconciliation manageable while preserving competitive tension. The final phase shifts toward structured stress testing under realistic growth and governance scenarios.

From Validation to Stress Testing

Finalist discussions should test structural durability.

Evaluate governance scalability as experimentation and personalization expand across properties. Test how the architecture performs in a multi-site or multi-brand environment with shared components and localized control. Examine data portability if strategic direction shifts. Assess how AI-generated content is governed, reviewed, and audited. Confirm that advanced capabilities can be deferred without requiring architectural rework or creating hidden dependencies.

This stage focuses less on feature confirmation and more on alignment with long-term operating models.

The Critical Checklist for DXP Evaluation

A disciplined evaluation model should answer:

  1. Have you separated platform evaluation from ecosystem design?
  2. Is weighting across both tracks defined before demos begin?
  3. Does the architecture align with your current operational maturity and support the governance structure you will require as scale increases?
  4. Does the vendor’s roadmap and acquisition pattern preserve your architectural autonomy over time?
  5. Can phaseable capabilities such as CDP be introduced deliberately, and does the architecture support evolving personalization and flexibility across vendor solutions?
  6. Have non-functional realities and full ecosystem costs been modeled early?

Composable and pre-composed DXPs represent architectural strategies along a spectrum. A structured two-track evaluation approach ensures that whichever model is selected, it is chosen for structural alignment and long-term outcomes rather than surface cohesion.

 


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Dan Drapeau
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