Platform expertise depth is the kind of thing every agency claims and almost no retailer evaluates rigorously. The conversation usually goes something like: “We have deep Magento expertise” / “Great, send the proposal.” Then the proposal arrives with case studies, certifications, and platform partner badges, and the retailer signs based on a general impression of competence. Six months later, when the agency hits an architectural decision they don’t have the depth to handle well, the retailer discovers what platform expertise actually means.
This is a guide to evaluating platform expertise depth before signing, when the retailer still has the leverage to ask hard questions and pick a partner who actually has the depth they claim. The evaluation isn’t complicated, but it requires asking specific questions and looking at specific artifacts rather than relying on general impressions.
Depth Is a Specific Thing, Not a General Thing
Before evaluating depth, it helps to be clear about what depth means in the eCommerce platform context. Depth includes hands-on experience across the full platform surface, frontend templating, backend customization, integration patterns, database design, deployment and operations, performance optimization, security configuration, and the specific quirks of the platform that experienced practitioners know about.
Depth shows up as the ability to answer specific technical questions without consulting documentation. The architect can explain how Magento’s EAV model affects query patterns and when to denormalize. The Shopify expert can explain when an app’s webhook architecture will hit rate limits and what the workaround is. The Hyvä developer can explain the trade-offs of Hyvä’s Alpine.js patterns versus alternative approaches.
Depth also shows up as the ability to handle the unusual cases that come up in real implementations. Standard catalog implementations are easy; configurable products with complex BOMs, multi-warehouse inventory with reservation logic, customer-specific catalog visibility, and tax calculation across multi-state operations are where depth matters.
Surface-level expertise can implement the standard cases. Depth handles the unusual cases without trial and error. Retailers want depth.
Ask for Specific Architecture Walkthroughs
The single most effective way to evaluate depth is asking the candidate to walk through a specific architectural decision from a prior engagement. The right question is concrete: “Tell me about an architectural decision you made on a comparable engagement that you’d handle differently in hindsight. What was the decision, what produced the issue, and what would you do now?”
Partners with depth answer this question with specifics, a particular client, a particular decision, a particular technical issue, and a clear articulation of what they learned. The answer demonstrates that the partner has done enough work to have learned, has the reflection capability to identify lessons, and has the operational discipline to apply those lessons to subsequent work.
Partners with shallow expertise either don’t have an answer (they haven’t done enough comparable work to have learned anything specific) or give a generic answer that doesn’t reflect real depth (“We always recommend more discovery now”).
The variation in answers between candidates on this question is often dramatic, and it correlates closely with how the engagement actually goes.
Examine Their Public Technical Contributions
Partners with real platform depth tend to have public technical contributions that demonstrate it. The contributions might be open-source modules, blog posts that go into actual technical depth (not marketing fluff), conference talks, community forum activity, or contributions to platform documentation.
The evaluation isn’t quantitative, having ten blog posts doesn’t matter if they’re all surface-level. The evaluation is qualitative, do the contributions show actual depth, working with real problems and real solutions? The agency that publishes substantive content about specific Magento performance issues, Hyvä migration patterns, or Shopify B2B implementations is signaling depth. The agency whose published content is generic platform marketing isn’t.
Public contributions also reveal the agency’s posture toward the community. Some agencies treat platform expertise as a competitive asset they hoard. Others treat it as a community resource they share. The community-engaged agencies tend to have stronger talent retention because their engineers value the public reputation that comes with the work.
Bemeir’s engineering team maintains a body of technical writing and community contribution because the team treats platform depth as something to develop and share openly, not protect.
Look at the Bench
The agency has a finite team. The depth on that team matters more than the depth they claim collectively. Two specific questions worth asking:
How many engineers does the agency have with deep expertise on the platform you’re hiring them for? Not generally familiar, deep expertise, the kind that handles unusual cases without trial and error. The number is usually smaller than retailers expect, and substantially smaller than the agency’s marketing implies.
What’s the engagement plan for those engineers on your project? Sometimes the deep experts are the ones who sell engagements but not the ones who execute them. The architect named in the proposal may be a fractional resource doing oversight while the actual work happens with less senior people. This isn’t necessarily wrong, but it should be visible during evaluation.
The retailers who ask these questions specifically tend to get better resourcing on their engagements, because the agency knows they’re paying attention.
Examine Their Approach to Platform Upgrades
Platform upgrade work is where depth shows. A Magento or Adobe Commerce upgrade involves understanding what changed between versions, what the upgrade path requires, what customizations need to be re-implemented or refactored, what breaking changes affect integrations, and how to manage the upgrade with minimum business risk.
Shallow expertise treats upgrades as scheduled work that proceeds linearly. Deep expertise treats upgrades as risk-managed projects with specific assessments, validations, and contingency plans. The difference shows up in the planning approach.
Specific questions worth asking: How do you assess upgrade complexity for a specific instance? What’s your approach to identifying customizations that will need re-implementation? How do you validate integrations after upgrade? What’s your rollback plan if upgrade produces unexpected issues? How do you handle data migration when upgrades affect schemas?
Partners with depth answer these specifically. Partners without depth give general answers that don’t reveal a structured approach.
| Depth Signal | What to Ask | What Weak Looks Like |
|---|---|---|
| Specific architecture decisions | Tell me about a decision you’d handle differently now | Generic answer or no answer |
| Public technical contributions | Show me your team’s published work | Marketing content only |
| Bench composition | How many deep experts on this platform? | “We have lots of expertise” |
| Upgrade methodology | Specific approach to upgrade assessment | “We just follow the standard process” |
| Performance methodology | Specific approach to bottleneck analysis | “We use the standard tools” |
| Customization patterns | Specific patterns for maintainable custom code | “We follow best practices” |
Test Their Performance Engineering Depth
Performance is a useful dimension to test because it requires specific platform knowledge and isn’t bluffable in a detailed conversation.
The questions that reveal depth on Magento or Adobe Commerce performance: What’s your approach to identifying database query bottlenecks? How do you handle Redis cache configuration for high-traffic sites? What’s your approach to optimizing checkout performance specifically? How do you handle catalog page performance for large catalogs? What’s your strategy for image optimization at scale?
On Shopify: What patterns reduce app overhead on storefront performance? How do you handle large catalog or theme template performance? What’s your approach to optimizing Shopify Plus B2B portals?
On Hyvä specifically: What’s the Alpine.js component pattern that scales for complex pages? How do you handle Hyvä compatibility issues with third-party modules? What’s the migration approach from Luma to Hyvä for a customized storefront?
Partners with depth answer these specifically with examples from prior work. Partners without depth give generic answers about caching and CDNs.
Test Their Customization Discipline
How an agency handles customization predicts how the platform will evolve over time. Depth involves disciplines that produce maintainable customizations; shallow expertise produces customizations that accumulate as technical debt.
Specific questions: What’s your pattern for adding custom logic to product save events? How do you structure custom modules so they survive platform upgrades? What’s your approach to overriding platform behavior cleanly versus invasively? How do you document customizations for future maintenance?
The right answers involve specific patterns, preference and plugin patterns in Magento, app patterns in Shopify, module structure that survives upgrades. The wrong answers involve general best-practices talk that doesn’t reveal an actual disciplined approach.
Retailers should ask to see customization code from prior engagements, with appropriate confidentiality protections. The code reveals the discipline more directly than any conversation.
Examine the Operational Handoff
Depth includes the ability to hand off operational responsibility to the retailer’s team after launch. Partners who can’t do this well typically have shallow expertise that depends on their own ongoing involvement to function.
Specific questions: What documentation do you produce for operational handoff? How do you train the retailer’s team on the implementation? What’s your support model after the implementation phase ends? How do you handle escalation when the retailer’s team encounters issues that exceed their depth?
The pattern that works for mid-market retailers is operational handoff that empowers the retailer’s team to handle routine work, with the agency available for issues that exceed in-house capability. The pattern that doesn’t work is dependency on the agency for routine operations.
What Bemeir Looks Like on These Evaluations
When candidates evaluate Bemeir on these dimensions, the team can show specific architecture decisions across hundreds of Adobe Commerce, Hyvä, and Shopify engagements (including ones the team would handle differently now and have learned from), a public body of technical content and community contribution, a documented bench with named expertise, a structured upgrade methodology, deep performance engineering across Magento and Hyvä, customization patterns that survive upgrades, and operational handoffs that produce self-sufficient retailer teams.
The team’s pattern is depth that comes from years of focused work on specific platforms rather than breadth across many. The hyper-specialization in Adobe Commerce, Hyvä, and Shopify is deliberate, because depth on a few platforms is more valuable for the retailers we work with than shallow familiarity with many.
Mid-market retailers evaluating platform expertise should look for this kind of evidence-based depth across candidates. The conversation reveals which agencies have it and which are claiming it without backing it up. The retailers who do this evaluation rigorously end up with engagements that produce durable platforms; the retailers who skip the evaluation often end up with engagements that produce ongoing operational issues. Useful starting points for technical reference include the Adobe Commerce developer documentation and the Hyvä Themes documentation.
