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.
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.
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.
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.
The same standard of work we run for every client — applied to a Madrid brand’s realities.
Full service detailFunnel 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.
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.
Tests built and QA'd across devices, browsers and your app stack, with flicker-free rendering and no measurable hit to Core Web Vitals.
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%.
Cart drawer, shipping thresholds, payment options, express checkout placement and post-purchase upsell, tested against AOV and revenue per session rather than clicks.
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.
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 scopedWe instrument the funnel properly first. Most stores have broken or double-counted events, and you cannot optimise against numbers you cannot trust.
Quant tells us where visitors leave. Qual tells us why. We combine analytics, replays and direct customer input before writing a single hypothesis.
Hypotheses are scored and sequenced so the highest-value, lowest-effort tests run first. The roadmap is shared and you can reorder it.
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.
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.
Anonymised under NDA. Figures pulled from the client’s own analytics.
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.
~$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.
“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%.”
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.
Prefer to write it out? [email protected] gets a real reply the same business day, Mon-Fri, 9am-6pm MT.