X-Ray of Liège E-Commerce 2026

Two hosting philosophies split the base

The two leading platforms, WooCommerce (43% of the base, 251 sites) and PrestaShop (34%, 198 sites), are open-source solutions that the retailer hosts and maintains itself: together, 78% of the shops. Shopify and Wix hold the other side, hosted services (SaaS) where the vendor takes on the infrastructure and the updates, in exchange for less control but less maintenance. Combined, they account for just 10% of the base here.

That autonomy handicaps nothing on the substance. On the angles that matter for acquisition, schema.org product markup (`Product`, `Offer`, `BreadcrumbList`), Google Merchant Center feeds, hreflang tags, WooCommerce and PrestaShop match a Shopify, natively or through mature extensions. The gap lies in the hosting and the configuration, not in the engine.

PrestaShop's dominance is no local quirk either: a French-born solution served by the regional agency network, it is the standard of French-speaking e-commerce. The contrast with Shopify's global weight betrays that anchoring, not a Liège lag.

What the platform really decides: who carries the debt

The dominant CMS decides who carries the maintenance and optimization debt for the next three to five years: patching a flaw, migrating a major version, rebuilding a payment funnel. When the operator is an SME with no dedicated technical team and no maintenance contract, that debt builds up silently, unpatched versions, abandoned extensions, performance that degrades. That is the real subject, not the name of the CMS, and it is the configuration the Liège retail base makes most likely.

Speed is the only criterion where the CMS measurably weighs

On raw performance, the gap is clear on desktop and goes in a single direction, hosted solutions ahead:

PrestaShop brings up the rear of the major CMSes on desktop, and Odoo sits at 54 on mobile. The mobile order, for its part, plays out within one to three points on small per-platform samples: making it a verdict would amount to over-reading statistical noise, and the hierarchy can only be stated honestly on desktop.

The desktop gap comes down to infrastructure, which SaaS optimizes by default. Self-hosting demands serious hosting (Redis or Varnish, OPcache), a configured cache and a connected CDN, three building blocks that many Liège retailers never switch on, for lack of a technical profile or a provider. Properly served, a PrestaShop or a WooCommerce closes most of it: what slows things down is the install, not the tool.

The platform name gives a tendency, it does not fix the result.

What each model really costs

The real cost of well-kept self-hosting, which this study does not measure, works out as an order of magnitude: performant hosting, dev time, modules on one-shot licenses of 50 to 100 euros apiece, so 2 or 3 k euros at install soon enough. On the other side, a Shopify Basic starts around 32 euros a month, apps and transaction fees on top. Open-source keeps a real structural advantage in exchange: ownership of the data, with no vendor lock-in and no Shopify Plus bill at roughly 2000 euros a month once at scale.

The real business divide sits in the checkout funnel. Shopify ships a native Checkout maintained by the vendor, whereas WooCommerce and PrestaShop leave a hand-built funnel, weakened after every update. That is where conversion is won or lost; the detail reads in the checkout journey layer.

The consequence is direct: the right question is not "did I choose the right platform?", but "am I exploiting the speed and the funnel it lets me reach?". The most profitable room almost always sits in optimizing what already exists (hosting, theme, images, third-party scripts), not in a migration.

Pages drag exactly where it counts most: on mobile. Belgium may remain a country where desktop holds on, 45% of visits across all sites according to StatCounter (opens in a new window), but online retail runs to another beat: 77% of traffic on merchant sites now arrives by smartphone, according to the Contentsquare benchmark (opens in a new window) built on 99 billion sessions. The screen where the Liège base is slowest is therefore the one almost every customer arrives through, and each marketing tool added digs the hole deeper. The finding hurts twice. In search first, speed feeding the signals Google uses to rank pages. In sales next, and the order of magnitude is worth knowing: when a page goes from 1 to 3 seconds of loading, the probability that the visitor leaves without doing anything rises by 32% according to Google's reference study (opens in a new window). A slow page drives away buyers the shop has often paid to bring in.

The mobile divide

The median mobile score sits at 60 out of 100, against 83 on desktop. Twenty-three points of gap, right where most retail visits happen. That 60 is a lab Lighthouse score, a simulation on a throttled network and processor that makes it comparable from one site to another, not to be confused with field Core Web Vitals (CrUX base, available here on 186 sites with enough traffic). One nuance matters: Lighthouse diagnoses, only CrUX data weighs into Google ranking.

The mobile distribution leans low. Just 3.7% of e-shops are in the green, against 32.9% on desktop, and 23.1% squarely in the red, that is 132 sites under 50. The base optimized for the big screen and let the small one slip.

LCP, the time it takes the largest visible element (often the product photo) to display, exceeds 4 seconds on 64% of sites, when Google recommends staying under 2.5 seconds, a threshold met by only 21% of the base. Visual stability, on the other hand, is healthy: CLS, which measures layout shifts during loading, stays good on 81% of sites. The design holds up, it is the technical weight that drags.

The more you equip, the more you slow down

Rank e-shops by the number of third-party tools detected (analytics tags, advertising pixels, chat widgets, consent banners). The trend contradicts the intuition that "better equipped" rhymes with "better built": the mobile median declines monotonically, with no reversal from one tier to the next, from 63 for sites with no tools at all to 48 for a full stack. Fifteen points. The slope also holds on desktop (from 87 to 70), at constant platform and across all districts, from Liège to Waremme.

Each script adds, in varying proportions:

• network: a DNS request, a TLS handshake and a round trip to a third-party domain, outside the site's cache and CDN. Multiplied by twenty third-party origins, the connection cost weighs down the start.
• a blocked main thread: most of these scripts run on the main thread, the one that paints the page and responds to clicks. It is the profile of a Total Blocking Time that swells as the tags pile up, and it foreshadows INP, the interactivity signal in the Core Web Vitals.
• the unpredictable: a third party, by definition, escapes the retailer's control. Its latency and its outage of the day become the page's own.

Correlation is not causation

The direction of cause and effect calls for caution: the most loaded tier rests on n=8 sites only, too thin to make it a law, and the correlation can run both ways. Heavy scripts slow the page, but it is also the most commercially mature sites that pile on the most tools without investing in performance in parallel. Tooling here is a marker as much as a cause. As for the link between slowness and lost sales, it is an external benchmark, the Google study cited above and Deloitte's Milliseconds Make Millions (opens in a new window) report, which puts at +8.4% in conversions the effect of a tenth of a second gained in mobile retail, not a result from this corpus: the Liège study measured neither conversion nor revenue.

Loading the tools better rather than removing them

The right reflex is therefore not to remove the tools, but to load them cleanly: deferred loading of non-critical scripts and, for measurement, a server-side pass that takes the essentials out of the browser. The exact architecture is detailed in the measurement layer. The three goals, reliable measurement, fast page and compliance, then stop pulling against each other.

A flattering score by absence of subject

Measured on the homepage, consent compliance splits into four grades. 41% of sites earn a grade A (235 sites), while 44% fall into the weak zone (grade C or D). Of those 235 grade A scores, 215 show no banner because they load no tracker to consent to: a good grade by absence of subject, not by control. Only twenty sites truly earn their A on active trackers.

The risk therefore reads in the crossover between active trackers and the absence of consent, not in the displayed grade: the exposed page is the one that loads its trackers before any choice by the user, with no CMP to capture it.

Consent is not fixed inside the CMS

Consent is not a WooCommerce or PrestaShop feature. It is a CMP (consent management platform, such as Cookiebot, Axeptio, Complianz), wired into the tag manager (GTM) and paired with Google's Consent Mode v2. You add it whatever the platform, and the real work lies in the wiring between those pieces, not in dropping the widget.

Installing a banner via a module or an all-in-one plugin handles the display, not the compliance. A banner that drops trackers before the click, or that does not make refusal as easy as acceptance, stays non-compliant with the GDPR and the ePrivacy directive: compliance is verified in the network, request by request, never by the presence of a vendor logo in the footer. The proof is in the sample: 97 sites equipped with a CMP stay at grade C or D, for lack of real blocking before choice. The legal framework is detailed by the CNIL (opens in a new window).

Consent Mode v2: only advanced mode unlocks modeling

Google's Consent Mode v2 comes in two forms. In basic mode, Google tags stay blocked as long as refusal holds: no signal goes out, refused conversions are lost. In advanced mode, tags load from the start but stay throttled without consent, and send anonymous pings (`consent denied`) that let Google model the missing conversions.

This modeling is subject to volume thresholds (traffic and conversions per country) below which Google reconstructs nothing, often out of reach for a small Liège e-commerce account. Across the sample, only 35 sites run a Consent Mode v2 in advanced mode: the only ones technically equipped to recover part of the conversions lost to refusal.

The figure of 83% of sites without Consent Mode calls for an honest reading. It includes 221 sites with no Google tag to steer (no Google Ads, no GA4 connected), for which the absence of Consent Mode is moot. Conversely, a site spending on Ads without a consent framework burns budget continuously.

Consent Mode only covers Google

Consent Mode only steers Google tags. The Meta Pixel, present on 101 sites, follows its own consent and server-side collection mechanics, detailed in the measurement layer: without them, social budget optimizes on holed data, exactly like Google budget without Consent Mode. At scale, it is the same server stream that decides both compliance and conversion reliability.

Half of Liège's stores have no idea where their sales come from, and some of those running ads pay against false numbers. Measuring accurately costs little and changes every decision that follows.

Google Analytics 4, the reference audience-measurement tool, shows up on only 293 sites, or 50.6% of the base: nearly one retailer in two knows neither on which pages its visitors drop off, nor where they abandon their cart. At the other end, 196 e-shops (33.9%) carry no measurement tool at all, no analytics, no pixel, no conversion tag: they run on guesswork. In between, 15.2% place a Google Ads tag; loaded without conversion wired, it counts visits but stays blind to the transaction.

Instrumentation that is rare and rickety

The most frequent marker remains the Meta Pixel, placed in pure client-side, with no server declaration to match. Yet a pixel alone, in 2026, is no longer a reliable measurement: between Apple's tracking prevention (ITP, which caps at seven days the lifespan of first-party cookies set client-side in JavaScript), ad blockers and the tightening of iOS, it lets slip 20 to 40% of events depending on the share of Safari/iOS traffic, or one to two purchases in five.

What is missing is the Conversions API (CAPI) to mirror collection server-side, out of reach of the blocker and of ITP, and above all an `event_id` shared between browser and server to deduplicate. Without this pair, you choose between two evils: under-counting (pixel alone) or double-counting (both without deduplication).

The hierarchy of the stack speaks louder than any figure on its own

• Universal Analytics still present: 101 sites (17.4%) load this version, shut down by Google in July 2023 (opens in a new window). It has collected nothing for nearly three years, but no one has removed it, because no one looks at the data: tracking installed once, never audited.
• The tag manager in the minority: 121 sites (20.9%), two and a half times rarer than the analytics it should orchestrate. As a common-sense approximation, roughly four GA4 installs in ten lean on it; the other six hard-code their tags into the theme, where every fix goes back through a developer. The layer that makes tracking maintainable is missing on eight sites in ten.
• Paid acquisition in the minority: Meta Pixel on 101 sites, Google Ads tag on 88 (15.2%). The same total of 101 for these two distinct tools is a coincidence, not a double count. That the advertising pixel is on a par with a dead Universal Analytics shows that the tag is sometimes installed before there is even a measurement foundation that holds.

What emerges from the whole is an absence of architecture, not of tools: the gap comes down to method more than to technology.

GA4 present does not mean GA4 that measures

A loaded tag does not make a measurement plan: you still need to track business events (`purchase`, `add_to_cart`, `begin_checkout`), feed cart and revenue through enhanced e-commerce and filter internal traffic. The 293 GA4 in the base are overwhelmingly default GA4, which counts page views without ever reading the funnel.

The cost is not only down to the ghost GA4. The 88 sites equipped with Google Ads and the 101 carrying a Meta Pixel optimize their media budget on false numbers: lacking Consent Mode v2, the conversions lost to refusal are no longer modeled, and without Enhanced Conversions or a deduplicated CAPI, the ROAS displayed understates real performance. To this is added the speed cost quantified in the performance layer.

The 2026 answer lies in the sequence

Server-side tracking answers both ills in a single move.

An sGTM, a tag server that brings measurement back to the retailer's side (via Stape or Addingwell), pulls GA4, the Meta Pixel and Google Ads out of the browser: the client gets lighter, first-party cookies gain lifespan, and the stream only carries what consent allows. It is the structural answer, to put in place after the foundations, never as a starting point: attempted too early on a rickety base, it adds complexity without fixing anything. The sequence reads as effort against impact.

• Remove the 101 dead Universal Analytics: five minutes per site, immediate weight savings, zero risk.
• GTM plus Consent Mode v2 on the 88 Google Ads and 101 Meta Pixel: this is where the leaky data costs cash. The step that secures compliance before investing more.
• A clean GA4 backed by a measurement plan: measure what you decide on, not everything.
• Server-side: for the volumes that justify it, last.

Our reading of this work is detailed on the expertises side.

The reading scale shifts here

We leave the 579 e-shops measured one by one and move down into the real buying journey, payment and delivery, read page by page on a sub-sample of 59 stores crawled in depth, the ones whose payment and delivery pages were actually readable. What follows therefore describes a frequency of presence, a ranking, a direction, never market shares. What we gain in granularity we lose in representativeness: the solid signals are the broad contrasts, the tight calls stay aside. We read the stores' technical shop window, their till stays shut, and that is exactly the reading a conversion audit lays down before touching anything else.

From payment to delivery, the portrait stays very local

At the till, the landscape leaves no ambiguity. Bancontact and bank transfer dominate, two methods anchored deep in Belgian habits, followed by invoice payment, PayPal, then the aggregator Mollie. The signature of a business that serves a local customer base first, and that takes payment the way it always has.

This leading duo says a lot about the buyer being targeted. Bank transfer, an amount and a reference to copy over then funds to wait for before the parcel ships, assumes trust already in place, not an impulse buy. Bancontact is the quintessential Belgian domestic reflex, smooth for anyone holding an account in the country, off the table past the border. Invoice payment confirms the reading: paying after receipt is something few pure players extend to an anonymous first-time buyer.

One misreading to dismiss right away: Mollie leading the field betrays neither immaturity nor local retreat. It is the de facto standard of Benelux e-commerce, the aggregator stores plug in to offer Bancontact, cards, wallets and local methods behind a single integration. PayPal, alongside, adds international reassurance.

On the delivery side, the same local tone. Shipping handled directly by the retailer comes ahead of Bpost, with the DPD and Mondial Relay pickup-point networks bringing up the rear. The study crawls delivery-option pages, without touching shipping volumes: it tells what stores offer, not how much they ship.

Payment filters, the funnel decides

The payment method goes beyond a technical step at the bottom of the funnel: it is a filter. On one side, stores plugged into an aggregator like Mollie or Stripe: the buyer lands on a standardized line-up and pays in a few seconds, within a journey already lived a hundred times elsewhere. On the other, those accepting only the classic bank transfer or Bancontact alone: a filter cut out for the buyer already in confidence, local and loyal to the brand.

This filter costs little to whoever targets only their regulars, and dearly to whoever would like to broaden out. For a lukewarm visitor, caught via a search or an ad, the absence of an immediate payment adds a step right when intent is at its most fragile; without measured sessions, abandonment stays the most likely scenario rather than an established fact. Of all the brakes observed, it is in any case the cheapest to release: plugging in an aggregator touches neither the catalogue, nor the positioning, nor the logistics, and bank transfer stays available as an option.

Payment, though, is only one step, and it is the whole funnel that decides the sale. Four points weigh as much as the payment method: forced account creation where a guest checkout would do; every superfluous field against a checkout condensed into a single page; shipping costs dropped at the final screen, the most documented cause of cart abandonment, around 48% according to the Baymard benchmark (opens in a new window); and Bancontact on mobile, where more than 60% of traffic flows, whose redirect to the app or QR code becomes real friction the moment the integration is botched.

The delivery page says neither where, nor how much

• Nearly 60% of the 537 commerce profiles state nowhere where or how the store delivers: no covered zone, no lead time, no price grid before adding to cart.
• When the info exists, it most often limits itself to Belgium, sometimes extended to neighbouring countries, rarely formalized into a standalone Delivery page that would carry weight.
• The visitor left in the dark leaves rather than writes in: a cart that never started, invisible in the statistics since nothing happened there that analytics could count.

Three clear lines on the delivery page demand neither a rebuild nor a budget.

In CRO, everything the buyer has to guess, they count as a risk.

A stated lead time, a named carrier, a free-shipping threshold on display, a readable returns policy: the page stops asking a question, it answers. This signal ties back to the click-and-mortar finding, where two thirds of e-shops have a store behind them: part of the traffic comes from people ready to collect in store, provided the page says so.

Three sales models coexist, to consumers, between professionals, or both, and none has pulled ahead.

Across the 491 e-shops segmented by their customer model (491 net profiles out of the 537 complete records, 46 set aside for lack of signals), the split holds in three families: 264 sell to consumers (B2C, 54%), 121 between professionals (B2B, 25%) and 106 mix both audiences (hybrid, 22%). None of the three models is marginal: there is no telling the story of Liège e-commerce as a purely consumer affair.

Nobody is mature, and that is the lesson

The three models share the same local fabric and equipment of the same order. Mean maturity index of 1.08 in B2C, 0.97 in B2B, 0.93 in hybrid: a single tool detected per segment at the median, and a maximum gap of 0.15 point, to read in relative terms, not as a hierarchy. Performance and compliance stay indifferent to the model too: median mobile perf of 60 to 61 everywhere, weak GDPR grades between 39% and 44%. The model changes neither the site's speed nor its compliance, which points to a common cause upstream, on the tooling and stack-choice side.

The best students tick two or three technical boxes, rarely more; the mass ticks zero or one. No leading pack, an entire fabric starting from the same place. Bad news for anyone looking for a local benchmark to imitate, excellent news for anyone wanting to get ahead.

Two reading caveats

The index aggregates four unequal signals: analytics, advertising pixels, marketing tags and consent banner. The banner, most often placed by default by the CMS or the theme, inflates the score while saying nothing about real measurement: when a profile's median comes out at a single tool, that point is frequently automatic consent, not deliberate tracking.

Second reservation, the bridge with the commerce layer. The 18% of sites exposing in-store pickup (n=491) and the 66% of establishments with a physical store (n=537) do not rest on the same subset: the 18% includes pure players devoid, by construction, of any pickup point. Figuring the "gap" on that scope would overstate the lag; the real dormant reserve sits in the intersection of store + site. The trend stays clear: a substantial share of retailers who also hold a store does not expose pickup on their site.

Choosing your audience, then your channel

Segmenting B2C, B2B or hybrid only has operational value once translated into an acquisition channel and a priority for action. You attack where the effort-to-impact ratio is highest.

• B2C (264 sites, 54%): non-brand Search on purchase intent, Meta for latent demand, web-to-store to bring people back in store. The volume quick win is here: in-store pickup is exposed by only 18% of them while the majority has a high-street presence, and plugging it in connects two assets already paid for, with no rebuild and no media budget.
• B2B (121 sites, 25%): tight intent-driven Search, LinkedIn to target the job function. Pickup stays an outlier between professionals (2%); the return comes from leads and quotes, form, lead tracking, scoring, integration with the CRM and invoicing.
• Hybrid (106 sites, 22%): the trap is serving both audiences the same way, a simple cart and a displayed price for the consumer, a quote on account and deferred invoicing for the professional. A generic site calibrated for neither imposes a permanent splits stance: the repositioning gets framed before any technical optimization.

The physical anchoring of Liège e-commerce

Across the 537 complete profiles analyzed, 354 stores, or 66%, lean first on a very real point of sale. These are click-and-mortar businesses: the click of the web grafted onto the brick of the high-street store.

If two thirds of the base are first stores, the gaps measured elsewhere, mobile slowness, compliance endured, the absence of measurement, reread as traditional retail at the start of its digitalization, not as negligence. What is mostly missing is time: running a store and a website at once, often alone, does not leave the room a pure player has.

Click & Collect sleeps in the back room

That same physical root points to the most telling missing piece: Click & Collect, the in-store pickup of an order placed online. The most natural bridge between the store and the site equips only 13% of Liège e-shops, all profiles combined. A retailer who already runs a counter, stock and opening hours owns the essentials: what they mostly lack is the online reservation and the promise kept at pickup.

The contrast with HTTPS, the basic encryption of a connection, near-universal at 577 sites out of 579, says a lot. When the foundation activates by default, asking nothing of the retailer, the base follows en masse; when you have to decide and wire it yourself, it drops off.

The realistic potential does not climb to 100% for all that: a poorly run Click & Collect, stock out of sync, fuzzy delays, disappoints more than it serves. The gap reads as a margin open to brands that have a point of sale, reliable stock and the rigor to keep the promise.

What the type of customer changes

Crossed by customer typology, the contrast holds: Click & Collect at 18% in B2C, 14% in hybrid, 2% in B2B, a breakdown detailed in the profiles layer. One nuance is worth keeping here: between professionals, the invoice and the delivery remain the norm, but for a local reseller, the spare part a tradesperson comes to collect urgently is a real use. Where it exists, the low rate owes less to sector fate than to a missed opportunity.

Wiring pickup is not enough

One caution remains: that Click & Collect is the most natural bridge for a physically rooted base is solid; that its installation mechanically generates growth remains a hypothesis, because the study observes equipment rates, not a single euro of revenue. To this is added a prerequisite that points straight back to the measurement layer: without reconciliation from online to offline, a customer who spots a product online then buys it on the shelf stays a black hole, and the impact of pickup stays invisible, therefore impossible to arbitrate.

Pickup, finally, only plays at the bottom of the funnel. The most profitable work often sits earlier, in local discovery: Google Business Profile listing, local SEO, store locator, store pages that rank on geo-targeted queries. Reducing web-to-store to Click & Collect alone means missing the top of the funnel, where digital truly brings the customer into the store.