CTOs lose Adobe Commerce platform decisions to CFOs more often than they should, not because the platform is wrong but because the business case was built in the wrong language. A CFO does not need to be convinced that Adobe Commerce is technically capable; they need to see a model that ties platform investment to revenue, cost, and risk in numbers the finance team can audit. The CTOs who succeed at platform decisions are the ones who build that model rigorously and present it on terms a CFO accepts. The CTOs who do not end up arguing about feature comparisons that the CFO is not equipped to evaluate.
This piece walks through the ROI framework Bemeir helps CTOs build when justifying Adobe Commerce platform investment to executive finance. The framework is the version that consistently wins approval at mid-market and enterprise scale; the structure is the same whether the investment is a new build, a major platform upgrade, or a replatform.
What the CFO actually needs to see
The deliverable that succeeds is a one-page summary with a supporting three-page model. The summary covers:
The decision. What is being asked of the business: capital, operating expense, timeline.
The expected return. Revenue uplift, cost savings, risk avoidance. Each with a stated assumption and a sensitivity.
The payback period. When the investment is recovered.
The downside case. What if the model is wrong; how bad does it get.
The status quo cost. What does doing nothing cost in revenue, cost, and risk over the same horizon.
A CFO will not approve the investment without seeing all five elements. A CTO who presents three of the five is not done.
Building the revenue side
Three categories of revenue impact from Adobe Commerce investment:
Conversion rate uplift from performance. Better Core Web Vitals produces measurable conversion improvements. The Web.dev performance research tracks the relationship at roughly 1% conversion lift per 100ms LCP improvement on mobile. A store moving LCP from 3.5s to 1.5s typically captures 8-15% conversion uplift in the first 6-12 months post-launch.
Feature-driven revenue. Specific platform features unlock revenue that the current platform cannot. B2B feature set unlocking enterprise customers that would not buy on a legacy platform. Cross-sell and upsell capabilities. Subscription functionality. Each feature should have a stated revenue model.
Market expansion revenue. Multi-store, international, multi-currency, or new channel capabilities that unlock markets the current platform cannot serve.
Churn reduction. B2B platforms with strong account features (account hierarchies, requisition lists, custom catalogs) reduce churn among enterprise accounts. The retention math is meaningful at scale.
The model should treat each revenue category as a separate line item with a base case, an optimistic case, and a downside case. The CFO can audit each separately.
Building the cost side
The cost categories the model needs to cover:
Implementation cost. The agency or in-house build cost: development, design, project management, testing, launch. Discrete dollar amount over the implementation timeline.
Platform licensing. Adobe Commerce license fees. Per environment, per year.
Infrastructure cost. Hosting, database, CDN, monitoring, third-party services. Monthly recurring at production scale.
Ongoing maintenance and development. The retainer or in-house engineering cost to keep the platform running and to ship roadmap features. Annual cost.
Migration cost (if replatform). Data migration, SEO preservation, customer communication, parallel-run period costs. Discrete cost over the migration window.
Training and change management. Internal team training, process changes, documentation. Discrete cost.
Cost savings vs status quo. What costs go away when the new platform is in place. Old platform licensing, redundant tools, manual processes that automation replaces. Annual cost savings.
The risk side
Risk modeling is what most CTOs underspend on and what CFOs most want to see. The categories:
Status quo platform risk. What is the probability and cost of major incidents on the current platform? Patch backlog risk. End-of-life risk if on a deprecated platform (Magento 1 stores, for instance). Compliance risk from outdated security posture.
Implementation risk. What is the probability and cost of the new platform implementation failing or going significantly over budget?
Adoption risk. What if the merchant team does not adopt the new platform features? What is the recovery plan?
Vendor risk. What is the platform vendor’s strategic commitment to the product? Is there a credible scenario where the vendor changes direction?
Each risk gets a probability and a cost. The expected value (probability × cost) becomes part of the comparison.
The full model structure
A clean ROI model has the following structure:
| Section | Content | Time horizon |
|---|---|---|
| Status quo projection | Current platform revenue, cost, risk over 3 years | Year 1, Year 2, Year 3 |
| Investment scenario | Implementation cost, new platform cost, expected revenue uplift, expected cost savings | Year 0 (investment), Year 1-3 (returns) |
| Net comparison | Difference between investment scenario and status quo per year | 3-year horizon |
| Payback analysis | Cumulative net cash flow showing when investment is recovered | Months from launch |
| Sensitivity analysis | What if revenue uplift is half of projected? What if implementation is 50% over budget? | Range of outcomes |
| Risk-adjusted NPV | Net present value with risk-weighted scenarios | 3-year NPV at appropriate discount rate |
The model presents in numbers. The narrative around the model explains the assumptions and the strategic rationale.
The assumptions that need defending
Three categories of assumptions where the CFO will pressure-test the model:
Conversion uplift assumptions. “Why do you believe LCP improvement will drive 10% conversion uplift?” The answer should reference: the current LCP and conversion baseline (your data), the projected LCP improvement (specific number from the new platform’s performance characteristics), the published research on LCP-conversion correlation, and benchmarks from similar stores that completed comparable migrations.
Implementation cost assumptions. “Why is the build $1.2M and not $2M?” The answer should reference: the scope document, the agency proposal with line-item breakdown, the assumptions about scope changes (typically 15-20% buffer for unknown scope evolution), and the historic performance of comparable agency engagements.
Maintenance and operations cost. “Why is annual OpEx $400K and not $700K?” The answer should reference: the retainer scope, the in-house staffing assumptions, the infrastructure cost projection, and benchmarks from comparable stores.
Assumptions that cannot be defended become risks in the model. The CFO appreciates seeing the risk acknowledged rather than smoothed over.
Three CFO-grade modeling principles
Be conservative in revenue projections. A model that promises a 20% conversion uplift gets discounted by the CFO. A model that promises an 8% uplift with strong evidence and a path to more gets believed. Win the credibility battle first.
Be exhaustive on cost. A cost projection that misses categories (training, change management, parallel run) gets flagged. Include every cost the program will actually generate; the credibility cost of one missing line item exceeds the budget cost of including it.
Present the downside honestly. A model that only shows the upside case is discounted. A model that shows the base case, the downside case, and the response plan for the downside case is believed.
The status quo case
The most important section of the model is often the status quo case. What does not investing actually cost?
For a store on an outdated platform, the status quo includes:
- Conversion that does not improve as competitors invest in performance
- Security and compliance risk from accumulating patch debt
- Engineering velocity that degrades as technical debt compounds
- Talent retention risk if engineers do not want to work on the legacy platform
- Strategic optionality that erodes if the platform cannot support new business directions
Quantifying each of these is harder than quantifying the upside, but the work is essential. A CFO comparing “spend $2M to upgrade” to “spend nothing” will sometimes pick the second. A CFO comparing “spend $2M to upgrade” to “lose $3-5M over three years from status quo” picks the first.
What good presentation looks like
The presentation that wins is not 60 slides. It is a 10-slide deck with a one-page executive summary, a clear model walkthrough, and a deliberate Q&A for the assumptions that matter most.
The model itself, the spreadsheet, should be auditable. The CFO’s team should be able to open it, change the input assumptions, and see how the output changes. Hardcoded outputs without traceable inputs lose trust.
What Bemeir brings to the ROI conversation
When CTOs ask Bemeir to support an internal platform business case, the contribution is usually in three areas:
Benchmark data. Conversion uplift, performance improvement, and migration cost numbers from comparable stores we have built. Generalizable to a degree, with explicit acknowledgment of where each store’s situation differs.
Implementation cost rigor. Honest line-item estimates that the CFO can audit, with the scope assumptions and risk premiums called out.
Operational cost projections. What does running the new platform actually cost in year one, year two, year three. Not just hosting but everything that touches operations.
The CTOs who win the platform decision usually do so by combining their own internal understanding of the business with the practitioner data the agency can provide. The combination is more credible than either alone.
The platform decision is ultimately a business decision dressed in technical clothing. The CTOs who learn to present it that way win the decisions they should win. The Adobe Commerce platform documentation and the agency proposals provide the technical detail; the ROI framework above is what bridges the technical detail to a CFO-grade business case. The work is well-understood; the variable is whether the CTO does the modeling work or hopes the technical merits speak for themselves.
