Proof

Just by running these tests, KoRRo generated more than €300,000 in additional revenue (This covers our agency fee for the next 2.5 years insane ROI).

And the best part? This didn't require a single euro of additional ad spend-we simply squeezed more out of their existing users.

KoRRo isn't an outlier. It's a simple example of what we consider our hygiene standard for delivering results. We deliver outcomes like these consistently.

Context & important market trends

E-commerce is in the middle of a massive crisis-there's no easy way to sugarcoat it.

Everywhere you look, headlines are filled with stories of companies going out of business. So, what's driving this turmoil?

How do you know if you're affected by these macro trends?

• You're hitting a revenue plateau.

• Your new customer acquisition rate is struggling.

• Your conversion rate is declining.

• Your average order value is dropping.

• And most painfully-your profit margin is shrinking by the week.

It's not your fault that the economy is turbulent. But it is your responsibility to understand what you can and cannot control. You can't:

• Change the economy.

• Control consumer behavior on a macro level.

• Bring back the days of cheap money.

But you can control how you react to these challenges. Over the past six years, here's what we've seen every time the market faced a crisis. Whether it was:

• COVID,

• The post-COVID decline,

• Or any other major disruption...

The companies that went out of business were the ones that played to survive. They blamed external factors and didn't even bother to look at what was within their control.

They made decisions out of panic-decisions that were rarely thought through. And the #1 mistake we've seen lead to bankruptcies and near-death experiences?

Focusing too much on retention. Which sounds a little counterintuitive, right? Isn't email/ CRM marketing supposed to be the most profitable channel? Yes – and no. During a crisis, most companies dive into their analytics to answer one question: What marketing channels are bringing in the most profit?

It's a good & fair to ask question. But the conclusions and actions taken are often disastrous. Companies tend to slash budgets on paid ads and start spamming their existing audience, squeezing every last penny out of them.

The problem?

They're ignoring the core issue:
Being profitable-or at least breaking even-on the first order.

Most companies don't think about the second-or third-order consequences of focusing solely on existing customers and slashing budgets:
Your existing customers will only buy so often. Without a steady inflow of new customers, you'll eventually run out of people to sell to.

Focusing on retention channels during a crisis isn't solving the problem-it's just postponing it. The real solution? Figuring out how to become profitable on the first order. And that's exactly where CRO plays a major role.

CRO helps you squeeze more money from the people you're already driving to your website. It doesn't rely on more ad spend or spamming your existing customers-it fixes the underlying issues holding your profitability back.

However they had never tested anything on their website. That's exactly why they brought us in. The next pages will take you behind the scenes and dive deep into the exact process we used to get them results fast.

Activity 1 CRO funnel alignment to find leaks

The first step was to fully understand customer journey. If the goal is to get as many people to buy as possible, you need to have an extremely deep understanding of why people are or aren't buying.

That's exactly the mindset you need when optimizing a funnel. To understand KoRRo's funnel as thoroughly as possible and get results fast we had to answer a few critical questions:

• Where are users coming from? (Which channel brought them in?)

• What framing and motivations do they have from the ads?

• When are they buying the products?

• Why are they buying the products?

• And a lot more...

Step 1: identify category entry points

Right now, you might be thinking, "What the hell are Category Entry Points?" Let me teach you something new really quick:

Category Entry Points (CEPs) are the key reasons, situations, or triggers that make your customers think about your category. In simple terms, they answer these six questions:

Category Entry Points are incredibly powerful when it comes to understanding why people actually buy your products.

For KoRRo, we needed to move fast. That meant we didn't have time to run surveys right away. Usually, we'd run surveys like these:

Instead, we had to rely on existing data. And luckily, we had access to something most brands don't. Something most brands can't build in-house.

A custom-built research tool designed to uncover consumer insights from massive data sets. Over the past five years, we've built on top of different Large Language Models to create tools that extract relevant insights from all kinds of data sources (very fast).

We're not selling this tool. It's exclusively for our customers, giving them an unfair advantage in the market.

Step 2: understand customer journey

Once we understood the audience and knew who we were selling to, the next step was to piece together the entire customer journey.

This required even more digging and research-and it's one of the most critical steps in the process.

It's also one of the most time-consuming parts of optimizing a website. Most people skip it because they don't have the time, the knowledge, or because they falsely believe it's irrelevant.

What am I talking about?

• Super in-depth funnel analyses

• Analyzing every heatmap on every page

• Watching 5+ hours of session recordings

The more data you collect on your audience and their behaviors, the better your insights and the higher the likelihood you'll uncover something that's costing you money that can be optimized. This is the formula that I personally use all the time:

f(CRO) = Frequency x Cost x Success Rate

The more data you have the higher the Success Rate. Let's dive into some of the things we analyzed and what we found. Spoiler we analyzed a lot. Let's look at some interesting finds we had:

These four insights are just the tip of the iceberg... Within just a few days, we uncovered 100+ insights into how users were navigating and interacting with the shop.

At this point, we had two critical things:

1. A clear understanding of who we were selling to and why they buy at KoRRo.
2. A detailed picture of the actual behavior of users in the store.

With the initial research complete and a solid grasp of how the funnel was performing, we went back to the drawing board to figure out the best ways to fix the drop-offs we had identified.

Activity 2 - decrease time to purchase to fix leaks

When it comes to fixing revenue leaks, the first step is understanding the behavior that leads to a conversion. Again, it's all about getting a deeper understanding of the problem and the mechanics behind it.

Here's the thing: purchasing behavior is complex.

• It's not simple.

• It's not linear

The best way to visualize it?

Stop thinking in funnels for a second. A user doesn't buy like that. Let me explain. A user will primarily buy your product for one of two reasons:

1. To solve a problem, or

2. To reach a specific desire.

However it's not a simple yes-or-no decision. The decision to buy is made up of many small decisions. A user needs to complete every single one of these decisions. From start to finish to make a purchase.

But here's the good news - This gives us tons of opportunities to optimize and get more people to buy.

You need to understand why the user isn't completing a specific decision. To figure out what's missing, we use a psychological behavior model that explains how decisions are made.

The BJ Fogg Behavior Model, adapted for conversion where:

f(Conversion) = Motivation X Ability X Trigger

This model is easiest to understand when visualized as a graph:

For a decision to happen three things need to align at the same time:

1. Enough Motivation

2. The Ability to Perform the Action

3. A Trigger

There's a direct relationship between motivation and ability. If motivation is low but the action is hard to perform, the behavior is unlikely to happen.

This leads to abandonment, stopping the customer journey, and ending the session without a conversion. Now, what exactly are motivation, ability, and trigger? Here's a quick explanation:

So, if we want to fix conversions, we need to focus on improving the outcomes of small decisions like:

• Searching for a product

• Adding a product to the cart

• Continuing to checkout

To fix abandonments at these decision points, we need to figure out which part of the equation is out of balance:

• Do users lack enough motivation?

• Is it too hard for users to complete the action?

• Is the trigger simply missing?

Now, let's look at some of the tests we ran and how we used this framework to improve results.

We focused on fixing issues and tapping into opportunities (based on the framework) to drive more sales.

Step 3: identify revenue leaks & opportunities

When it comes to identifying revenue leaks and opportunities, ideas are rarely the problem. The real challenge is testing the most impactful ones.

After completing all the research, we put our ideas into our prioritization engine. This is essentially a formula that ensures we test the ideas that:

• Have the highest potential revenue uplift,

• Are most likely to succeed, and

• Are the least difficult and costly to build.
  

For KoRRo, we used a more sophisticated prioritization engine that factored in everything we needed to move fast and leverage all the data we had. Here's what we prioritized:

• Where the test will run (revenue exposure)

• How many people will see the test (scroll depth = revenue exposure)

• What research indicators we have (success rate)

• Ease of implementation (cost)

• Our database of 2.5K experiments (success rate)

This process helped us identify the highest-priority ideas - the ones most likely to drive more revenue. Next, we asked ourselves:

How can we use the Fogg Behavior Model to best fix the issues or tap into new opportunities? Let's walk through some of the tests we ran & the thought process behind them.

We found that certain fields in the checkout were causing hesitation. Specifically:

• Birthday

• Country & State

Once we identified these issues, we started brainstorming potential fixes.

Our idea?

• Hide the non-essential fields

• pre-select options where possible

• Move non-critical data collection, like the birthday field, to a post-purchase step bundled with a small incentive.

When you're fixing an issue, you should always frame your idea as a hypothesis. Why Because you need to test if it actually works or not.

A hypothesis forces you to think carefully about what you want to try and challenges your assumptions. Here's the structure we use:

• IF we change XYZ

• THEN we expect metric XYZ to improve

• BECAUSE this change should trigger behavior Z and help more people complete their decision

For this test, our hypothesis looked like this:

• IF we reduce/remove optional form fields (date of birth & federal state) in the checkout and preselect "Netherlands" in the "Country" field,

• THEN the average revenue per visitor increases,

• BECAUSE users will experience less cognitive and physical effort to enter all relevant information and can proceed to the next checkout step more quickly. Additionally, reducing the number of optional fields allows users to focus more on the purchase process, leveraging fluency and cognitive ease.

See what we did there? We focused on ways to make the ability easier. And we accomplished that by also tapping into some cognitive biases.

If you're struggling to identify behavior patterns or cognitive biases you can use as triggers to optimize a decision, this is a great resource:

Once we had the hypothesis, we handed it off to our design team. Here's how the process worked. First The design team prototyped the solution. Then the development team built it.

After that the quality assurance team ensured there were no bugs or issues. Once cleared by QA we finally, we put it live as a test:

If you are unfamiliar with how a proper A/B test works, Here’s a quick overview:

This test ran for almost two months to ensure statistical validity. (More on how we handle statistics in another document-link coming soon.) The result? A 0.88% uplift in revenue. It might not sound like much at first, but for a 9-figure brand, this small tweak added almost €1 million in additional revenue.

One test literally paid for our agency fee for the next five years. Now that's a ridiculous ROI. Let's move on to another test – this time, one we ran in the cart:

In the cart, KoRRo already showed users how much more they needed to spend to get free shipping. But the execution was far from ideal.

The element didn't really fit. Especially on mobile. It took up too much space, making the cart feel crowded and messy. This might seem like a small issue, but it's actually a big deal.

The human brain is lazy. The harder it is to focus or the less clear something is, the more likely the brain will get exhausted or bored and "switch off."

When that happens, the brain stops putting energy into the task of purchasing, leading to cart abandonment.

Our hypothesis:

• IF we change the progress bar for shipping costs in the cart drawer and on the cart page,

• THEN the average revenue per user increases,

• BECAUSE: Users have a clearer overview of their products and can more easily recognize when they're close to free shipping. Users are motivated to add more products to minimize shipping costs. The urge to reach a goal (free shipping) becomes stronger the closer the user gets to the goal - thanks to the goal gradient effect.

According to the hypothesis our design team did some magic: