The conversion case for Hyvä migration tends to get pitched in two registers: either as a vague performance improvement (“your site will be faster”), or as a specific number borrowed from a single retailer case study (“we delivered 22% conversion lift”). Neither version is particularly useful to a buyer trying to model the migration’s actual ROI on their own business. The first is too soft to base a budget decision on. The second is real but unrepresentative, every Hyvä migration is different, and the spread of outcomes across retailers is wider than most case studies admit.
This article describes what the conversion lift actually looks like across the population of Hyvä migrations Bemeir’s Hyvä practice has executed, what drives the variation, which scenarios outperform the median, and which scenarios consistently under-perform. The framing here is statistical rather than anecdotal, and the goal is to give a CFO or CMO enough information to make a defensible budget decision.
The median outcome
Across mid-market Adobe Commerce retailers, defined here as $5M to $50M in annual revenue, with mobile-dominant traffic and non-trivial Luma customization, the median Hyvä migration produces:
- 50-65% reduction in Largest Contentful Paint on mobile
- 60-80% reduction in Interaction to Next Paint
- 35-50% improvement in Lighthouse mobile performance score
- 5-10% improvement in mobile conversion rate at six months post-launch
- 2-4% improvement in desktop conversion rate at six months post-launch
- 8-15% improvement in mobile add-to-cart rate
- 3-7% improvement in average order value (a secondary effect, faster sites have lower checkout abandonment)
These are median outcomes, meaning half of retailers will see better and half will see worse. The spread is wide. The top quartile sees mobile conversion lift in the 12-20% range. The bottom quartile sees 2-4%. Both ends of the distribution are explainable, and the explanations matter for any retailer trying to estimate where they will land.
What drives the variation
Five variables explain most of the variation in Hyvä migration outcomes.
Pre-migration mobile performance. The single biggest driver. Retailers whose pre-migration mobile LCP was above 4 seconds consistently see larger conversion lift than retailers whose pre-migration LCP was already in the 2-3 second range. The reason is mechanical: there is more conversion to recover when the starting point is worse. Retailers in the worst pre-migration performance band tend to see 12-18% mobile conversion lift; retailers already in the “fine but not great” band tend to see 4-7%.
Mobile traffic share. Hyvä’s largest performance gains are on mobile. Retailers whose traffic mix is 70%+ mobile see materially larger total conversion impact than retailers whose mix is 50/50 or desktop-dominant. The desktop conversion lift is real but smaller, typically 2-4%.
Frontend customization preserved. A Hyvä migration that preserves the brand’s existing visual design, with all custom components, sees smaller conversion impact than a migration that takes the opportunity to also clean up UX problems on the old Luma site. The difference is not the migration; it is the redesign that often accompanies it. Retailers who treat Hyvä as a pure technical migration and keep the existing UX patterns see smaller lifts. Retailers who use the migration as a forcing function for UX improvements see larger lifts.
Third-party extension footprint. Retailers with twenty or more extensions, especially extensions with heavy frontend customization, often see smaller performance lifts because the extensions reintroduce some of the JavaScript weight that Hyvä was designed to eliminate. The fix is to audit extensions during the migration and retire the ones that are no longer pulling weight.
Post-launch performance discipline. The Hyvä baseline is fast, but the post-launch trajectory depends on engineering discipline. Retailers who add third-party tracking scripts, heavy chat widgets, or unoptimized images post-launch lose some of the lift over the following six months. Retailers who maintain performance discipline preserve the gains.
| Variable | High-impact case (top quartile) | Low-impact case (bottom quartile) |
|---|---|---|
| Pre-migration mobile LCP | > 4.5 seconds | < 2.5 seconds |
| Mobile traffic share | > 70% | < 50% |
| Redesign during migration | Yes, UX overhaul bundled in | No, pure technical migration |
| Third-party extension count | < 10 well-curated | > 25, including heavy ones |
| Post-launch performance discipline | Performance budget enforced | No performance discipline |
| Typical mobile conversion lift | 12-20% | 2-4% |
What the conversion lift translates to in revenue
For a mid-market Adobe Commerce retailer with $20M in annual revenue, with 65% mobile traffic mix and a 1.8% mobile conversion rate, a median 7% mobile conversion lift translates to roughly $900,000-$1,000,000 in incremental annual revenue. Against a Hyvä migration cost of $120,000-$180,000, the payback period sits in the four-to-seven month range, and the three-year cumulative value is in the $2.5-3.0M range before considering compounding effects.
This is the math that makes Hyvä migrations one of the most reliably high-ROI technology investments available to mid-market Adobe Commerce retailers. The reason is that the underlying mechanism, faster mobile experience drives higher conversion, is well-understood, the cost is bounded, and the variance across retailers is in the size of the win, not in whether there is a win.
According to Akamai’s research on eCommerce performance, every 100ms improvement in mobile page load correlates with 1% improvement in mobile conversion across the retail benchmark. Hyvä migrations typically deliver 2,000-3,000ms of LCP improvement on mobile. The math compounds.
What over-performs the median
Three retailer profiles consistently produce conversion lifts well above the median:
Premium DTC brands with mobile-first audiences. These retailers tend to have aspirational mobile-first audiences, high baseline traffic, and elastic conversion that responds well to performance improvements. The combination produces 12-18% mobile conversion lift consistently.
B2B retailers with slow Luma frontends. B2B Magento storefronts have often accumulated more customization than consumer-facing ones, and the performance starting point is usually worse. The Hyvä migration produces dramatic relative improvement, sometimes 15-25% on the buyer-side workflow conversion, which translates to meaningful B2B order volume.
International retailers with slower network conditions. Retailers serving markets outside Tier-1 network conditions see disproportionate Hyvä benefit because the JavaScript reduction matters more on slower connections.
What under-performs the median
Three profiles consistently produce lifts below the median:
Retailers who treat Hyvä as a pure backend migration. If the migration preserves every existing UX pattern, every existing extension, and every existing tracking script, the performance lift is smaller and the conversion lift follows.
Retailers with very fast pre-migration performance. A Luma storefront that already had aggressive performance work done, server-side rendering optimization, careful third-party script management, image CDN with WebP, has less room to recover. The migration is still worth doing for maintenance and code modernization reasons, but the headline conversion number is smaller.
Retailers who add complexity post-launch. A clean Hyvä launch followed by six months of adding heavy chat widgets, tracking pixels, and personalization scripts can lose half the performance gain. The discipline post-launch is part of the ROI story.
What to measure and when
The right measurement cadence for a Hyvä migration is six points: pre-migration baseline, two weeks post-launch, six weeks post-launch, three months post-launch, six months post-launch, twelve months post-launch. The reason for the cadence is that conversion lift is not instantaneous. The performance change is, but the conversion response takes weeks to stabilize as users adapt to the new experience and as search rankings adjust to the improved Core Web Vitals signals.
The metrics worth tracking are: mobile and desktop conversion rate, mobile and desktop LCP and INP, bounce rate by device, add-to-cart rate, average order value, and revenue per session. According to the Google Core Web Vitals documentation, the conversion impact of CWV improvements is realized over a six-to-twelve week window for most retailers.
Honest expectation setting
The honest pitch for Hyvä migration is this: for most mid-market Adobe Commerce retailers, the migration produces 5-10% mobile conversion lift, pays for itself in four to nine months, and improves the platform’s operational maintainability for the next three to five years. Some retailers will see 15-20% lift. Some will see 3-5% lift. The 22% case studies exist but they are not the median, and a CFO should not budget against them.
The retailers who get the best return from Hyvä migrations are the ones who go in with realistic expectations, who use the migration as a forcing function for UX improvements rather than treating it as a pure technical port, and who maintain performance discipline after launch. Bemeir’s Adobe Commerce performance practice sees this pattern consistently: the migration is a tool, and the conversion lift depends on how the tool gets used.
