Conversion studio · Shopify
More revenue from the
traffic you already pay for.
LabsCodex is a conversion rate optimisation studio for premium Shopify brands. We research why buyers hesitate, test the fixes, and report the revenue — including the experiments that lose.
- Fixed-fee audit
- Roadmap is yours to keep
- No retainer commitment to start
- Experiments shipped
- 400+
- Win rate, reported openly
- ~26%
- Client-owned data and code
- 100%
Experiments shipped
Win rate, reported openly
Client-owned data and code
Trusted by premium Shopify brands
What we do
Four ways we move your conversion rate
Almost every brand starts with research and grows into a programme. All of them keep the research, the tests and the code.
- 01
Conversion Research
Analytics, session replay, user testing and heuristic review, turned into a ranked list of what is actually costing you revenue — with the size of the prize attached to each one.
Read moreAnalytics, session replay, user testing and heuristic review, turned into a ranked list of what is actually costing you revenue — with the size of the prize attached to each one.
Moves A ranked roadmap, with a revenue estimate on every hypothesis
- 02
Experimentation
Hypothesis-driven A/B and multivariate testing, built without flicker and analysed to a proper statistical standard — including the tests that lose, which we report.
Read moreHypothesis-driven A/B and multivariate testing, built without flicker and analysed to a proper statistical standard — including the tests that lose, which we report.
Moves Sitewide conversion rate and revenue per session
- 03
Shopify Build & Speed
Theme, PDP, cart and checkout work on Shopify Plus and Hydrogen — fast, accessible, and instrumented so the next experiment takes days rather than weeks.
Read moreTheme, PDP, cart and checkout work on Shopify Plus and Hydrogen — fast, accessible, and instrumented so the next experiment takes days rather than weeks.
Moves Mobile conversion rate, Core Web Vitals, time-to-ship a test
- 04
Lifecycle & Retention
Average order value, repeat rate and lifetime value work — bundles, subscriptions, post-purchase flows and lifecycle messaging, tested with the same rigour as the site.
Read moreAverage order value, repeat rate and lifetime value work — bundles, subscriptions, post-purchase flows and lifecycle messaging, tested with the same rigour as the site.
Moves Average order value, repeat rate, lifetime value
How we work
One month of research, then a programme that compounds
No tactics before evidence, and no test called before it is ready. The first month establishes where the revenue is leaking; everything after that is a cycle of proving what fixes it.
- 01Weeks 1–3
Research
We interview your team, work through analytics and session replay, run moderated tests with real buyers, and review the funnel end to end. No changes yet — first we find out where the money is leaking, and why.
You receive
A written research report, annotated funnel, and recorded user sessions - 02Week 4
Roadmap
Every finding becomes a testable hypothesis, scored on expected impact, confidence and effort, with a revenue estimate attached. You get a ranked backlog you could hand to any competent team — including your own.
You receive
A scored backlog with revenue estimates — yours to keep either way - 03Ongoing
Experiment
We build, QA and ship tests against that backlog, with the metric and sample size agreed before launch. Results are analysed properly and written up either way, whether the variant won or lost.
You receive
A written result for every test, including the ones that lose - 04Quarterly
Compound
Winners get rolled permanently into the theme, losers get documented so nobody retests them in eighteen months, and the whole programme is reviewed against revenue rather than percentage lifts.
You receive
A quarterly review of programme contribution, net of our fee
Selected work
Programmes that moved the number
Every engagement below started with research rather than a redesign — and the losing tests are counted in the totals.
- Beauty2025
Rebuilding a product page around what buyers actually asked
High traffic, high bounce, and a product page written for the brand rather than the buyer. Research found four recurring hesitations; two quarters of testing answered them.
- product page conversion rate
- +14.2%
- revenue per session
- +9.1%
- tests shipped, the rest documented
- 6 of 23
product page conversion rate
revenue per session
tests shipped, the rest documented
- Home & furniture2025
Cutting a five-step checkout down to what people needed
A considered purchase with a long deliberation cycle was being handled like an impulse buy. We rebuilt the cart and checkout around delivery certainty.
- checkout completion
- +11.6%
- revenue per visitor
- +6.4%
- steps to purchase
- 5 → 2
checkout completion
revenue per visitor
steps to purchase
- Fashion2024
A mobile site that stopped losing people before it loaded
Four in five sessions were mobile and the page took almost five seconds to render. The fastest conversion win available was not a test at all.
- mobile LCP, 75th percentile
- 4.8s → 1.9s
- mobile conversion rate
- +21%
- repeat purchase rate
- +13%
mobile LCP, 75th percentile
mobile conversion rate
repeat purchase rate
Measurement standard
How we decide a test actually won
Most disputed conversion results come from the same handful of mistakes — a metric chosen afterwards, a test stopped early, a fortnight that happened to contain a payday. This is the standard we hold, on every experiment, without exception.
- Primary metric
Agreed before launch
Chosen with you and written down before the test goes live, so nobody goes hunting for a metric that won after the fact.
- Sample size
Calculated up front
We power the test for the effect we expect to detect, then run it to that number rather than stopping the moment a variant looks ahead.
- Significance
95%, two-tailed
Sequential analysis where we need to check progress early, so peeking does not quietly inflate the false positive rate.
- Minimum runtime
Two full business cycles
Whole weeks, so weekday and weekend buying behaviour are both represented before we call anything.
- Implementation
Server-side or theme-native
No flash of original content, and no measurable cost to Core Web Vitals. Speed is a conversion factor, not something we trade away.
- Reporting
Every test, win or lose
Written up in an archive you own, so nobody in your team retests the same idea in eighteen months' time.
- Attribution
Revenue, net of our fee
The programme is judged on what it contributed after our invoice, not on a percentage lift in a slide deck.
If a current or prospective agency cannot tell you their equivalent of this table, that is worth knowing before you sign anything.
How we operate
Four commitments we don't negotiate
They cost us some revenue and win us the clients we want.
Evidence before opinion
We do not ship changes because a competitor did it or because someone senior prefers it. If we cannot point to the research behind a hypothesis, it does not go on the roadmap.
We report the losers
Roughly three in four tests fail to beat control. An agency reporting a 90% win rate is either measuring badly or telling you what you want to hear, and both cost you more than the truth.
Measured in revenue
A lift on a micro-conversion is not a result. We report what the programme contributed in money, net of our fee, and we would rather that conversation be uncomfortable than vague.
You own everything
The research, the test code, the event layer and the analytics all live in your accounts. Ending an engagement with us should never mean losing what you have learned.
Questions
The things people ask before the first call
A design agency is paid to produce a new experience; we are paid to find out whether it performs. Both are legitimate, but they answer different questions. If you already know what you want built, hire the design agency. If the honest position is that nobody can say why the current site underperforms, research and testing will get you there for less than a redesign — and will tell you which parts of the redesign to keep.
Research takes three to four weeks, and the first experiments go live shortly after. Individual tests usually need two to four weeks to reach a decision, so the first shipped winner typically lands in month two or three. Anyone promising a lift in week one is not measuring properly.
No, and we would be cautious of anyone who does. We guarantee the process — research before hypotheses, metrics and sample sizes agreed before launch, honest analysis afterwards — and we report the programme's contribution in revenue so you can judge it yourself. Guaranteeing outcomes on a statistical process only works if you are willing to misreport results.
Then we will be the ones to tell you, at the quarterly review, in revenue net of our fee. It happens — usually because the constraint was never the site. If that is where we land, the useful outcome is knowing where the real bottleneck is, and we would rather end an engagement honestly than keep invoicing against a number nobody is checking.
Because anything shorter cannot produce a trustworthy result. A single test needs two to four weeks to reach significance, roughly three in four fail to beat control, and winners need time to be built and validated. A three-month engagement would let us run a handful of tests and report noise. The minimum protects the quality of the answer, not our revenue.
As a rough guide, around 8,000 sessions and 300 orders a month per tested template makes a normal A/B programme viable. Below that we lean on research, higher-impact changes tested one at a time, sequential analysis, and painted-door tests rather than pretending we can detect a 3% lift. If your traffic will not support a programme yet, we will say so on the first call.
For research and most of the site, no. It matters for checkout: Checkout Extensibility and script-level customisation are Plus features, so on standard Shopify we focus on everything up to checkout — which is usually where the larger opportunity sits anyway.
Usually, yes. Most of our clients have an in-house team and often a creative or media agency. We tend to own research and the experiment programme, and either build the winners ourselves or hand your developers a specification and the test code. We are not looking to displace people who are already doing good work.
You do, entirely. Everything runs in your Shopify store, your testing tool and your analytics accounts. At the end of an engagement you keep the research archive, the full test history including the losers, and the code — so the next team starts from what you have already learned instead of retesting it.
Start here
Find out what your store is actually losing.
Most engagements start with a conversion audit: three to four weeks of research into where revenue leaks in your funnel, and a ranked roadmap of what to test first. The findings are yours to keep, whether you run them with us or not.
- Reply within one business day
- A strategist, not an SDR
- We'll tell you if you're not ready to test