Frequently Asked Questions

The RPV Growth Sprint is designed for established Shopify brands with meaningful traffic, getting at least 600 orders and doing around $100,000 per month.
That want to generate more revenue from the visitors you already have.

It’s best suited to brands that are already investing in acquisition and have enough customer activity for us to test changes reliably.

If your store is still early, has inconsistent sales or doesn’t yet have enough traffic to run meaningful A/B tests, our Shopify Foundations service may be a better fit. LINK

The RPV Growth Sprint is a 90-day optimisation program focused on increasing how much revenue your Shopify store generates from every visitor.

We research where revenue is being lost, develop changes across your customer journey, and A/B test those changes against your existing store.

The goal is not simply to increase orders. It’s to improve the overall value of your traffic by increasing conversion rate, and average order value.

Revenue Per Visitor, or RPV, is the average amount of revenue your store generates for every visitor to your site.

It simply measures how efficiently your website turns your traffic in to revenue.

It combines two important ecommerce metrics:

Conversion rate × Average order value = Revenue Per Visitor

For example, increasing your conversion rate can increase RPV. Increasing how much each customer spends can increase RPV too.

By looking at both together, we can focus on how much revenue your existing traffic is actually producing.

Because a higher conversion rate doesn’t always mean a more valuable store.

You could increase conversion by heavily discounting products, for example, while simultaneously reducing average order value or margin.

RPV gives us a broader measure of performance because it considers both how many visitors buy and how much they spend.

The aim isn’t to ship the most boxes. It’s to make every visitor more valuable.

Traditional CRO agencies focuses on selling more stuff, where we focus on making you more money.

We take a broader approach.

We look for opportunities across conversion rate and average order value, which could include your messaging, offers, user experience, navigation, product pages, bundles, upsells, cart experience and other parts of the buying journey.

And rather than simply making changes because they look like “best practice”, we test significant changes against your existing store wherever possible so we can see what actually produces more revenue.

No, you are paying for an outcome, not hours spent.

You’re engaging us to increase Revenue Per Visitor, not to deliver a predetermined number of A/B tests, design changes or development hours.

Some stores may reach the target through a small number of significant wins. Others may require more experiments.

We decide what to investigate, what to test and in what order based on where we believe the strongest revenue opportunities are.

Kozler brings together the strategy and implementation required to identify, create and verify improvements across your Shopify store.

Depending on what we uncover, that can include:

• Ecommerce and customer journey analysis
• Conversion strategy
• Offer and monetisation strategy
• UX and interface design
• Conversion-focused copywriting
• Shopify development
• A/B testing
• Experiment reporting and performance analysis

We don’t hand you a list of recommendations and leave your team to figure it out. We research the opportunity, develop the solution and test it ourselves.
So your team can focus on what it does best building and marketing your amazing products.

A successful A/B test generally needs around 200–300 orders per variation, so we recommend a minimum of around 600 orders per month.

If you’re not there yet, Shopify Foundations may be a better fit.

We guarantee a cumulative 10% increase in Revenue Per Visitor, verified through A/B testing.

If we don’t achieve that during the sprint, we continue working for an additional 90 day period at no extra cost.

Once the agreement is signed and payment is complete, we begin onboarding and gathering what we need to understand your store properly.

That includes access to your Shopify store, analytics and other relevant platforms, along with the information we need about your products, customers, marketing and current priorities.

From there, we begin our research and identify the first opportunities we want to investigate and test.

The 90-day period itself doesn’t begin when you sign,it begins when your first A/B test goes live.

Your 90 days begin on the day your first A/B test goes live, not the day you sign the agreement or begin onboarding.

That gives us time upfront to understand your store, research the opportunities and prepare the first experiment properly before the clock starts.

We need enough input to understand your business and enough cooperation to keep the work moving.

Depending on what we’re working on, we may ask you to:

• Complete questionnaires or workshops
• Provide information or content
• Give feedback on proposed changes
• Approve work before it goes live
• Let us know about upcoming promotions, campaigns or significant store changes

You don’t need to manage the optimisation process yourself, but we do need timely access to the knowledge and decisions only your team can provide.

We are Shopify optimisation experts but you are experts on your brand. We need to work together for the best results.

You don’t need your entire company sitting in meetings with us.

Ideally, we work with someone who understands the commercial priorities of the store and can provide or coordinate approvals when required. Depending on your business, that might be a founder, ecommerce manager, marketing lead or another senior decision-maker.

Other members of your team can be brought in when their expertise or approval is needed.

We ask that requested feedback, approvals or content are provided within five business days wherever possible.

A/B testing relies on keeping work moving and maintaining a stable testing environment, so long delays can slow the program down.

If something remains outstanding beyond five business days, testing may need to be paused until we have what we need to continue.

We use our team of professionals to look over your site and research where your store is leaking revenue and look for opportunities to improve conversion rate, and average order value.

We make assumptions and from there, we prioritise projects using the I.C.E matrix.

Then prototype changes and verify their impact against your existing store through A/B testing.

We use an ICE matrix to prioritise the opportunities we identify.

Each opportunity is assessed against three factors:

Impact — the potential impact on performance
Confidence — how confident we are in the opportunity
Ease — how easy it is to implement and test

This helps us compare potential opportunities and decide what to test first.

A/B tests can compare changes to website assets, design, copy or themes against the existing live experience.

Each experiment is classified as one of three types:

• Conversion Rate Test
• Average Order Value Test
• Full RPV Test

The type of test determines the primary metric used to judge its performance.

During an A/B test, live traffic is split between two versions:

The Baseline — your existing store experience.

The Challenger — the new version being tested.

Both versions run during the same period and their performance is measured using eligible traffic and orders. This allows us to measure the difference in Revenue Per Visitor between the two versions, to find the one that makes you the most money.

Yes.

Before a test launches, Kozler prepares an Experiment Brief that records the type of test, its primary metric, any secondary metrics and the target confidence level.

Each test runs for a minimum of 14 consecutive days and 600 orders, unless both parties agree in writing to end it earlier due to technical issues, data quality problems or significant changes in traffic.

A test may run for longer than 14 days if there isn’t enough traffic or order volume to reach the required confidence level.

There is no fixed number of tests.

It may depend on your order volume but generally 1- 2 tests per month.

You are engaging Kozler to achieve the RPV growth outcome rather than to deliver a set quantity of tests, hours or deliverables.

Some programs may reach the target with fewer tests while others require more.

When we run an A/B test, we look at statistical significance, essentially, how confident we are that the result is real and not simply due to chance.

As a guideline, we generally look for:

• Quick tests — 80%: Lower-stakes changes such as copy tweaks, button colours or minor layout adjustments.
• Core tests — 90%: Standard tests such as page redesigns, new sections, cart changes or checkout flows.
• Critical tests — 95%: High-stakes changes such as major site changes, pricing tests or checkout overhauls.

The bigger the potential impact of the change, the more confidence we want in the result before rolling it out.

Confidence levels are calculated using our A/B testing software and Kozler’s testing tools.

Kozler may declare a test inconclusive if the data is compromised, the test cannot be reliably measured, or its confidence level is below 50%.

Tests below 50% confidence do not count towards the RPV Growth Target and Kozler is not required to deploy that test to the live store.

Winning tests contribute towards the cumulative RPV Growth Target.

Where a test qualifies as a Winning Test, the test can be deployed to the live store.

If you choose not to deploy a Winning test, the test is still credited towards the RPV Growth Target as if it had been deployed.

You shouldn’t make, or allow another party to make, unapproved changes that could affect testing.

This includes changes to the store theme, checkout, customer-journey apps, core offers, sitewide pricing or discounts, tracking, pixels or analytics configuration.

If an unapproved change affects a test, Kozler may pause the affected test or exclude the affected period from the guarantee calculation.

We measure the performance of the existing version of your store against the new version at the same time, using live traffic.

For each test, we measure the change in Revenue Per Visitor and calculate the confidence level of the result.

This allows us to measure the impact of the change itself rather than simply comparing your store’s performance from one month to another.

Which adds in outside factors like economy and seasonal changes.

If a test produces a positive RPV result, it is credited towards your cumulative 10% RPV Growth Target and the winning version is deployed to your live store.

Not every test will produce a positive result.

If a test has a confidence level below 50%, or the data is compromised or cannot be reliably measured, Kozler may declare it inconclusive. An inconclusive test does not contribute towards the 10% RPV Growth Target and Kozler is not required to deploy the Challenger.

Only qualifying Winning Tests contribute towards the guarantee.

Each winning test is statistically weighted before it contributes towards your 10% RPV Growth Target.

It wouldn’t be fair for us to claim the full uplift from a test if the confidence in that result is lower.

For example, if a test shows a 10% RPV increase at 80% confidence, we credit 8% towards your target, not the full 10%.

When there is more than one winning test, those credited improvements are compounded together towards the cumulative 10% target.

Your total revenue can change because of factors such as seasonality, advertising spend, promotions and changes in traffic.

Instead, we use controlled A/B testing, where the existing version and the new version are tested at the same time against live traffic.

The difference between their performance allows us to measure the RPV lift attributable to the change being tested.

Yes. We never do trust me bro reporting?

You’ll have access to the reports and experiments used to measure the performance of your store and the tests we run.

Each test also has an Experiment Brief documenting its test type, primary metric, any secondary metrics and target confidence level before it launches.

Rather than claiming the full uplift from every positive A/B test, we probability-weight the improvement based on how confident we are in the result.

For example, if a test shows a 10% increase in Revenue Per Visitor at 80% statistical significance, we count 8% towards your 10% target — not the full 10%.

Tests generally run for a minimum of 14 days and around 600 orders, so we have enough data to make a meaningful assessment without letting tests drag on unnecessarily.

The verified improvements from each successful test are then added together towards your cumulative 10% RPV target.

This gives you a more conservative, statistically grounded view of the improvement we’ve actually achieved.

We keep working.

Reaching the cumulative 10% RPV Growth Target satisfies the guarantee, but it does not end the program.

Kozler continues working through the remainder of the initial 90-day period.

If we haven’t achieved the cumulative 10% Credited RPV Increase by the end of the initial 90 active days, the Extension Period begins automatically.

We continue working towards the target for up to another 90 active days at no additional fee.

The free Extension Period is capped at a maximum of 90 additional active days.

At the end of that extension, the guarantee is considered fulfilled whether or not the 10% RPV Growth Target has been achieved.

Ultimately if we don' t hit the target you walk away knowing you have a highly optimised store and 3 months of A/B testing for free.

This is never happened yet. So we very confident we can get you at least a 10% RPV growth of you met our criteria.

The RPV Growth Guarantee applies only to the first 90-days of this program, unless otherwise agree upon.

Any subsequent program, renewal or future engagement must be agreed separately in writing.

There isn’t a fixed ratio. It depends on how optimised your store already is.

A less optimised store may see more tests win because there are more obvious opportunities for improvement. As your store becomes more optimised, winning tests can become harder to find.

That isn’t a bad thing. A losing test tells us not to roll out a change that could make your store perform worse, while also helping us understand what is already working.

For a highly optimised store, even a small number of winning tests can make a meaningful difference to revenue.

We’re not against ads. Keep your ads running.

Advertising brings people to your store. Our job is to make the store more profitable once they get there by increasing how much revenue you generate from each visitor.

If your website isn’t converting or customers aren’t spending enough when they buy, simply sending more traffic to the same experience doesn’t address what is happening after the click.

RPV Growth focuses on improving conversion rate, average order value, or both, so the traffic you’re already paying for becomes more valuable.

Yes you can, but be aware that this is a job that requires a lot of different specialist skills to do it correctly.

In general bringing it in-house will not have a return on investment - unless your store is earning over $30-$50 million per year. Given that an expert term will cost upwards of $500,000 a year.

Kozler specialises in Revenue Per Visitor optimisation and brings together the different disciplines required to do the work: strategy, UX, conversion-focused copywriting, visual design, Shopify development, offer and monetisation strategy, and A/B testing.

Sometimes a store needs significant changes, but RPV Growth isn’t based on assuming that a complete redesign is the answer.

Once your store is doing over a one million in revenue per year website changes with out data can be very risky.

We research where revenue is being lost, prototype changes and test those changes against your existing store.

The goal is to identify and verify changes that increase Revenue Per Visitor rather than replacing the entire website simply for the sake of having something new. (sometimes a new website can under perform the old one if not done carefully)

A change to your website is a financial decision, and that decision becomes more important as your store grows.

For every $1 million in annual revenue, a 1% change in performance is a $10,000-a-year decision, in either direction.

Without A/B testing, you can’t really know whether the change itself made the difference. Comparing one month to another introduces outside factors such as seasonality, economic conditions, marketing campaigns and changes in buying behaviour, which can skew the results.

A/B testing lets us compare the existing experience and the new version at the same time, so we can see whether the change itself actually makes you more money.

Site optimisation isn’t always a one-off project. As your store grows, it becomes an ongoing system of testing, learning and improving. Think of it like going to the gym: doing it once doesn’t mean the work is finished. 

If you’ve tried A/B testing before and it didn’t work, there are multiple reasons why that may have happened.

It could be the strategy, the tests being run, the expertise of the team, the amount of traffic or the way the program was managed. A/B testing itself isn’t simply a software exercise, the thinking behind what you test and why matters.