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.
San Antonio, TX
Conversion Rate Optimisation in San Antonio, TX
Structured experimentation for San Antonio stores where the biggest wins are usually fit guidance, shipping maths and the second language.
Delivered remotely for brands across San Antonio and Texas.
Grow · San Antonio
Why San Antonio brands come to us for this
- Funnel analysis segmented by language, because Spanish-session drop-off is usually invisible in a blended report
- Fit and sizing experiments on boots, hats and leather aimed at conversion and return rate together
- Free-shipping threshold tested against modelled landed cost by zone rather than a number picked by feel
- Military discount sequencing tested as an offer: visible early, verified late, measured on new customers won
- Mobile checkout tested against visitor traffic patterns around graduation weeks and Fiesta, not just an annual average
Most CRO programmes in this city do not begin with a button colour. They begin with a funnel that leaks in three specific, unglamorous places: the shopper reading in Spanish who hits an English checkout, the boot buyer who cannot work out whether to order a D or an EE, and the shipping cost that appears three steps too late on a case of sauce or a 500-pound pit. Those are not micro-optimisations. They are the difference between a store that converts and a store that collects traffic.
We start with research rather than a test queue: session replays split by language, site-search logs, checkout drop-off by step, and the support inbox — which in San Antonio is a very rich source, because the same four questions arrive daily in both languages. From that comes a ranked list of friction points with revenue attached, and a roadmap where every hypothesis has a stated sample size before it runs.
The testing discipline is the same as anywhere: pre-declared samples, a defined stopping rule, flicker-free implementation that does not damage page speed, and an honest read when a variant loses. What differs is the subject matter. Here the highest-value experiments tend to touch fit confidence, freight transparency, discount sequencing and language coverage, because those are where South Texas stores are losing orders that they have already paid to attract.
Local context
Test the second language, the fit decision and the freight quote
Three local frictions produce most of the recoverable revenue we find here. The first is bilingual drop-off: in a Hispanic-majority metro a meaningful share of sessions are reading in Spanish, and when the funnel switches back to English at the size guide, the shipping policy or the confirmation email, they abandon at a rate nobody is measuring because the analytics were never segmented by language. The second is fit. Boots, hats and leather are decided on width, last and break-in, and a size chart PDF does not answer that — better on-page guidance reduces both abandonment and the return that follows. The third is freight and weight. Cases of salsa and large cookers carry real shipping cost, and a free-shipping threshold picked by intuition either loses money on every order or scares off the cart. We model landed cost per zone first, then test the threshold and the way it is communicated, rather than testing a number that was never defensible. And around Lackland graduation weeks, a spike of out-of-town visitors browsing on phones makes mobile funnel behaviour worth reading separately from the annual average.
Scope
What Conversion Optimisation includes
The same standard of work we run for every client — applied to a San Antonio brand’s realities.
Full service detailPrioritised 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.
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.
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%.
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.
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 San Antonio store
We do not work off a rate card. Every San Antonio 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 scopedHow it runs
From kickoff to results
Measure
We instrument the funnel properly first. Most stores have broken or double-counted events, and you cannot optimise against numbers you cannot trust.
Research
Quant tells us where visitors leave. Qual tells us why. We combine analytics, replays and direct customer input before writing a single hypothesis.
Prioritise
Hypotheses are scored and sequenced so the highest-value, lowest-effort tests run first. The roadmap is shared and you can reorder it.
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.
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
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
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, 2025FAQ
Conversion Optimisation in San Antonio — your questions
Yes, and you should. They are different audiences with different objections, and a blended result hides both. We segment sessions by language from the start, run experiments where volume supports it, and where the Spanish segment is too small for its own test, we treat it as qualitative research instead — replays and support tickets tell you plenty without pretending to statistical significance.
It is, if you count net revenue rather than orders. A page that persuades someone into the wrong width has not converted, it has borrowed. We test width and last guidance, break-in expectation, model measurements, fit feedback from previous buyers, and comparison against brands the customer already owns. Success is a lift that survives the return window.
By treating it as an offer with a measurable job rather than a permanent courtesy. We look at whether it brings genuinely new customers or mostly discounts people who were buying anyway, test where the offer is stated versus where verification is requested, and check the margin impact on the categories it is applied to. Sometimes the answer is to keep it and move it; occasionally it is to narrow it.
It affects how you read results, not whether you can run them. A test that starts before Fiesta and ends during it is measuring the event, not the change. We align test windows to whole, comparable periods, avoid concluding across a demand spike, and where a peak is unavoidable we run it as a holdout or push the read to the following cycle. Rushing a conclusion into a seasonal swing is how false winners get shipped.
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 San Antonio 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.