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Conversion Rate Optimisation in Madrid

A structured test programme for Madrid stores, built around the friction that is specific to Spanish and cross-border checkouts.

Delivered remotely for brands across Madrid and Spain.

Grow · Madrid

Why Madrid brands come to us for this

  • Payment method set and ordering tested — Bizum, cards and instalments — instead of assumed from the gateway default
  • Delivery estimates tested per destination: peninsula, Balearics, Canaries and EU, each with its own honest promise
  • Size and spec friction addressed on the page for footwear, perfumery and padel catalogues before it becomes a return
  • Experiment windows planned around the rebajas and August so results measure the change, not the calendar
  • Reyes gifting behaviour tested separately from self-purchase, because the buyer and the deadline are different

The most expensive conversion problems in a Spanish store are rarely on the product page. They sit in the last two screens, and they are usually about recognition. A shopper who reaches checkout and sees only card fields reads the store as foreign before she has read the total. Bizum has become an ordinary way to pay online in Spain, instalment options carry real weight on higher order values, and the order those methods appear in is testable rather than obvious. We treat the payment option set as an experiment surface, not a plugin decision made once.

The second cluster is the delivery promise. Madrid sits at the centre of the national distribution network, so peninsular delivery expectations are fast — and the same store also ships to the Balearics, the Canaries, Ceuta and Melilla, and increasingly across the EU, where the promise is completely different. Stores that show one estimate for all of it either overpromise and eat the complaints or underpromise and lose the order. Making the estimate honest, specific and visible before the cart is one of the more reliable wins available here.

The third is sizing and specification, which is category-shaped. Footwear and leather goods lose orders and gain returns on EU-to-UK-to-US conversion. Perfumery loses them on concentration and volume ambiguity. Padel loses them on weight, balance and shape being buried below the fold when they are the entire basis of the purchase decision. We research where the leak actually is with session data, site search and support tickets, then test against revenue per session rather than against a click.

Pre-declaredsample size and duration agreed before a test starts, no calling at 80%
Per-destinationdelivery promise tested separately for peninsula, islands and EU
Sale periods excludedrebajas weeks kept out of samples that span a pricing regime change
Local context

You cannot test a discount programme through the rebajas

Spain runs two structural discount periods a year, and they distort everything a test programme depends on. During the January and summer rebajas, intent, basket composition and price sensitivity all shift at once, so a result read across the boundary is measuring the calendar rather than the change. We plan around it: pricing, urgency and offer tests get run inside a single trading regime, structural tests — navigation, PDP layout, checkout flow, delivery messaging — get run in the full-margin stretches between sale periods, and August comes out of the sample entirely because the city empties and the traffic mix stops resembling the rest of the year. The gifting run into 6 January gets its own treatment: it is a different buyer with a deadline, and tests that win against a self-purchase audience in October are not guaranteed to hold against someone buying a Reyes gift on 3 January.

Scope

What Conversion Optimisation includes

The same standard of work we run for every client — applied to a Madrid brand’s realities.

Full service detail
01

Conversion Research Sprint

Funnel analysis, session replays, heatmaps, on-site polls and user tests across your top revenue templates. Output is a ranked list of friction points with revenue attached.

02

Prioritised Test Roadmap

Every hypothesis scored on impact, confidence and effort, with the projected revenue and required sample size stated up front. You always know what runs next and why.

03

Experiment Build & QA

Tests built and QA'd across devices, browsers and your app stack, with flicker-free rendering and no measurable hit to Core Web Vitals.

04

Statistical Analysis

Pre-declared sample sizes, sequential-testing guardrails and segment-level readouts by device, traffic source and new versus returning. No peeking, no calling a test at 80%.

05

Checkout & Cart Optimisation

Cart drawer, shipping thresholds, payment options, express checkout placement and post-purchase upsell, tested against AOV and revenue per session rather than clicks.

06

Monthly Programme Report

Tests run, results in full, cumulative revenue impact and what the results taught us about your customers. Losers are reported in the same detail as winners.

Scoped and quoted for your Madrid store

We do not work off a rate card. Every Madrid engagement starts with a fixed statement of work — named deliverables, named dates, one number — written after we have looked at your store, not before. If a smaller first step would serve you better, we will say so.

Get this scoped
How it runs

From kickoff to results

01

Measure

We instrument the funnel properly first. Most stores have broken or double-counted events, and you cannot optimise against numbers you cannot trust.

02

Research

Quant tells us where visitors leave. Qual tells us why. We combine analytics, replays and direct customer input before writing a single hypothesis.

03

Prioritise

Hypotheses are scored and sequenced so the highest-value, lowest-effort tests run first. The roadmap is shared and you can reorder it.

04

Test

Two to four concurrent experiments depending on traffic, each run to a pre-declared sample size. No test gets stopped early because it looks good on day three.

05

Implement & Compound

Winners get hard-coded into the theme, losers get documented, and every result feeds the next round of hypotheses. The programme gets smarter each month.

Proof

Conversion Optimisation results

Anonymised under NDA. Figures pulled from the client’s own analytics.

Premium Skincare (DTC)

8-figure DTC brand, ~140 SKUs, US + CA · Shopify Plus (migrated from Magento 2)

Magento 2 cost $9k a month in hosting, extensions and emergency dev before a single feature shipped. Mobile LCP sat at 5.4 seconds and mobile converted at less than half the desktop rate across 68% of sessions. The named constraint: 11,412 indexed URLs and a top-3 organic position on their hero category, so a migration that lost rankings would cost more than the platform ever saved.

+41%mobile conversion rate1.62% to 2.28% over the first 90 days post-launch
5.4s → 1.8smobile LCP75th-percentile CrUX field data, not lab
+27%organic sessionssix months post-migration vs. pre-migration baseline, branded queries excluded
$108k/yrplatform cost removedhosting, extension licences and the standing emergency dev retainer
Engagement Replatform + CRO retainerTimeframe 7 months (4-month migration, 3-month optimization)

Performance Apparel (DTC)

~$6M/yr DTC, 900+ SKUs across size and colour variants, US · Shopify Plus

Returns ran at 31% and refund cost consumed the entire paid media margin. One size chart image served 40 different fits, and 62% of add-to-carts started on a collection page that never showed variant availability. The named constraint: no new product photography budget, so every fix had to come out of the existing asset library and the review corpus.

+29%sitewide conversion rate1.71% to 2.21%, five-month average
+14%average order value$84 to $96 once the threshold bar and cross-sell shipped
31% → 22%return ratenine-point drop, roughly $310k/yr in recovered margin
1.9x → 2.4xblended MERwith paid spend held flat throughout
Engagement Conversion-led rebuild + paid mediaTimeframe 5 months
In their words

Clients on this work

CVR 1.9% → 2.7%

“We'd been running our own tests for a year and calling every 3% swing a win. The first thing they did was tell us our sample sizes were garbage, which was not a fun call to sit through. Six months later we're getting wins that actually hold up when you re-measure them. Sitewide CVR went from 1.9% to 2.7%.”

Founder & CEOApparel DTC brand, ~$12M/yr · Los Angeles, CA
Verified client, 2025
FAQ

Conversion Optimisation in Madrid — your questions

It is worth testing rather than assuming, and the honest answer is that the effect is usually about recognition more than mechanics. A Spanish shopper scanning the payment row for something familiar makes a trust judgement in the first second, and the presence and position of a domestic method feeds that judgement. We test the option set and its ordering, and we measure it on completed revenue rather than on clicks into the payment step.

It complicates it, and ignoring it is the real problem. Mixed-market traffic means a test can win overall while losing badly in a segment that matters, usually because delivery cost or language quality differs by country. We declare the primary segment before the test, size the sample against it, and read results by market as well as in aggregate. Where one market is too small to reach significance on its own, we say so rather than pretending the aggregate answers for it.

It makes returns policy a conversion asset rather than a legal footnote. EU consumers have a statutory withdrawal period on distance sales, so the question is not whether you accept returns but how clearly and confidently you say so, and who pays the return shipping. We have seen clarity on that point matter more than the terms themselves. It is a genuinely testable element on the PDP and in the cart, and it interacts with the size and fit work in categories like footwear.

Yes, but the programme runs differently. If the rebajas carry a large share of your year, the work in the months before them is about preparing the store to convert that spike — checkout speed, stock and size visibility, delivery clarity under load — and the work during them is measurement rather than experimentation. Then the between-sale periods become where structural tests run at full margin. Concentrated seasonality changes the schedule, not the value.

Around 40,000 sessions and 800 orders a month is where a testing programme becomes statistically viable. Below that, tests take months to reach significance and you are better served by research-led redesign work and analytics fixes. We will tell you honestly which bucket you are in.

The first test goes live in week three, after research and instrumentation. Meaningful cumulative impact typically shows around month four, once six to ten tests have run. CRO is a compounding programme, not a one-month fix, and anyone promising otherwise is selling best practices.

Some do, and that is normal. A loser is still information: it rules out a hypothesis and sharpens the next one. We report losses in the same detail as wins because a programme that only ever produces winners is one that is not being measured properly.
Next step

Conversion Optimisation for your Madrid brand.

Thirty minutes with the strategist who would actually run your account. We screen-share your store, read your data live, and tell you the three highest-value things we can see from the outside.

Shopify or Shopify Plus stores doing $150k/mo or moreFounder, CEO or eCommerce lead on the callNo deck and no pitch — we open your store instead

Prefer to write it out? [email protected] gets a real reply the same business day, Mon-Fri, 9am-6pm MT.