Turn website improvement ideas into measured commercial decisions
Once you fix the obvious bugs on your website, the harder questions start. Will showing trade pack pricing on category grids increase order value or confuse single-item buyers? Does a two-step quote form bring in better enquiries than a single long page? Guessing in meetings or copying competitors' layouts without measuring the result can easily reduce conversions while making the site look newer. - Website changes get pushed live without a clear baseline, making it impossible to tell whether they helped or hurt sales. - Testing tools are used to spin up minor button-colour experiments that run for months without reaching a real conclusion. - Low-traffic pages are put into A/B split tests that can never reach statistical confidence in a realistic timeframe. - Higher click-through rates get celebrated as "wins" even when completed orders or sales-accepted enquiries actually fell. Agentix runs ongoing conversion rate optimisation (CRO) and experimentation programmes for UK eCommerce, B2B and trade businesses. Part of our [website conversion services](/services/website-conversion), we combine research, clean [tracking and reporting](/services/tracking-reporting) and disciplined test design so every website change leaves you with a verified commercial answer.
Knowing when to run an A/B test and when to ship a direct fix
In our experience, treating every website improvement as an A/B split test is just as wasteful as never testing at all. If a payment button fails on Safari or a form validation error hides off-screen on mobile, you don't run a four-week experiment to see if customers prefer a working button. You fix it immediately. And if a page only gets a few dozen conversions a month, a standard split test will take a year to detect a modest uplift. Here is an illustrative decision guide with invented round numbers (not a client result) showing how sample-size maths (at **95% statistical confidence and 80% power**) shapes the right method for each change: | Monthly visitors to the journey | Baseline conversion rate (monthly conversions) | Visitors needed per variation to detect a 10% relative lift | Time required for a 50/50 split test | Best commercial approach | | -- | -- | -- | -- | -- | | 80,000 visitors | 2.5% (2,000 conversions/mo) | ~61,500 visitors (~123,000 total) | ~6 weeks | **Controlled A/B split test.** Traffic supports testing a specific checkout, pricing or layout hypothesis cleanly. | | 25,000 visitors | 2.0% (500 conversions/mo) | ~78,000 visitors (~156,000 total) | ~6 months
Where CRO and testing programmes go wrong in practice
When an experimentation programme chases "test velocity" or software badges instead of commercial outcomes, the same traps appear: | What goes wrong in testing programmes | What is happening underneath | What it costs your decisions and revenue | | -- | -- | -- | | A "winning" test is rolled out, and monthly revenue doesn't budge | Someone called the test early as soon as the chart flickered past 95% confidence in week one ("peeking") | You build permanent site changes around random statistical noise rather than real buyer behaviour | | Form conversions jump 30% in a test, while sales complains leads are worse | The test measured raw Submit clicks or stripped out a qualifying field without tracking CRM acceptance as a guardrail | Sales wastes hours sorting through unusable enquiries while the testing dashboard claims a victory | | Tests run for three months and end up inconclusive every time | Split tests are being run on low-traffic templates or tiny visual tweaks that cannot move the needle | You pay for a monthly testing retainer and software licence without learning anything actionable | | An eCommerce test increases order count, while gross margin falls | A prominent discount
How an ongoing Agentix CRO cycle runs
Rather than launching random variations to look busy, we run a structured cycle tied to your commercial goals and development capacity: 1. **Evidence and hypothesis first.** Every proposed change starts with a specific problem observed in your funnel data, customer support questions or UX task checks, paired with a clear prediction of what will change and why. 2. **Primary metric plus commercial guardrails.** Before any test or staged release goes live, we lock the decision rules: the primary completion metric (such as completed orders, revenue per visitor or sales-accepted enquiries) and the guardrails that must not be harmed (such as average order value, refund rates or lead quality). 3. **Clean build, QA and honest reporting.** We coordinate or build the test variations, verify them across mobile and desktop browsers, and report the outcome straight, including when a hypothesis did not beat the control so your team knows not to waste engineering time building it permanently.
Frequently asked questions
### What if our website doesn't have enough traffic for traditional A/B testing? We will tell you upfront rather than selling you split tests that can never reach significance. Where traffic is lower (common on specialist B2B and trade sites), we focus your improvement cycle on observed task research, high-leverage form and journey fixes, and carefully instrumented before-and-after releases with clear guardrail checks. ### How do you stop an experiment from hurting lead quality or order margin? We never judge a test on shallow clicks alone. For eCommerce tests, we track revenue per visitor, basket composition and order completion alongside conversion rate. For B2B and trade enquiry tests, we connect test variations to your [customer data and CRM records](/services/customer-data-systems) so we can see whether the new version produced genuine sales-accepted quotes. ### Which A/B testing tools and platforms do you work with? We work with modern experimentation setups (including VWO, Convert, custom server-side or feature-flag splits, and platform-native testing tools on Shopify and custom builds). If you don't already have a testing tool, we will advise whether your traffic volume a
Speak to us about an ongoing CRO programme
Whether you have the traffic to run disciplined A/B experiments or want a structured monthly programme to research, fix and measure your highest-value customer journeys, we can help.